Podcasts about datahub

Shawn Tierney meets up with Connor Mason of Software Toolbox to learn their company, products, as well as see a demo of their products in action in this episode of The Automation Podcast. For any links related to this episode, check out the “Show Notes” located below the video. Watch The Automation Podcast from The Automation Blog: Listen to The Automation Podcast from The Automation Blog: The Automation Podcast, Episode 248 Show Notes: Special thanks to Software Toolbox for sponsoring this episode so we could release it “ad free!” To learn about Software Toolbox please checkout the below links: TOP Server Cogent DataHub Industries Case studies Technical blogs Read the transcript on The Automation Blog: (automatically generated) Shawn Tierney (Host): Welcome back to the automation podcast. My name is Shawn Tierney with Insights and Automation, and I wanna thank you for tuning back in this week. Now this week on the show, I meet up with Connor Mason from Software Toolbox, who gives us an overview of their product suite, and then he gives us a demo at the end. And even if you’re listening, I think you’re gonna find the demo interesting because Connor does a great job of talking through what he’s doing on the screen. With that said, let’s go ahead and jump into this week’s episode with Connor Mason from Software Toolbox. I wanna welcome Connor from Software Toolbox to the show. Connor, it’s really exciting to have you. It’s just a lot of fun talking to your team as we prepared for this, and, I’m really looking forward to because I just know in your company over the years, you guys have so many great solutions that I really just wanna thank you for coming on the show. And before you jump into talking about products and technologies Yeah. Could you first tell us just a little bit about yourself? Connor Mason (Guest): Absolutely. Thanks, Shawn, for having us on. Definitely a pleasure to be a part of this environment. So my name is Connor Mason. Again, I’m with Software Toolbox. We’ve been around for quite a while. So we’ll get into some of that history as well before we get into all the the fun technical things. But, you know, I’ve worked a lot with the variety of OT and IT projects that are ongoing at this point. I’ve come up through our support side. It’s definitely where we grow a lot of our technical skills. It’s a big portion of our company. We’ll get that into that a little more. Currently a technical application consultant lead. So like I said, I I help run our support team, help with these large solutions based projects and consultations, to find what’s what’s best for you guys out there. There’s a lot of different things that in our in our industry is new, exciting. It’s fast paced. Definitely keeps me busy. My background was actually in data analytics. I did not come through engineering, did not come through the automation, trainings at all. So this is a whole new world for me about five years ago, and I’ve learned a lot, and I really enjoyed it. So, I really appreciate your time having us on here, Shawn Tierney (Host): Shawn. Well, I appreciate you coming on. I’m looking forward to what you’re gonna show us today. I had a the audience should know I had a little preview of what they were gonna show, so I’m looking forward to it. Connor Mason (Guest): Awesome. Well, let’s jump right into it then. So like I said, we’re here at Software Toolbox, kinda have this ongoing logo and and just word map of connect everything, and that’s really where we lie. Some people have called us data plumbers in the past. It’s all these different connections where you have something, maybe legacy or something new, you need to get into another system. Well, how do you connect all those different points to it? And, you know, throughout all these projects we worked on, there’s always something unique in those different projects. And we try to work in between those unique areas and in between all these different integrations and be something that people can come to as an expert, have those high level discussions, find something that works for them at a cost effective solution. So outside of just, you know, products that we offer, we also have a lot of just knowledge in the industry, and we wanna share that. You’ll kinda see along here, there are some product names as well that you might recognize. Our top server and OmniServer, we’ll be talking about LOPA as well. It’s been around in the industry for, you know, decades at this point. And also our symbol factory might be something you you may have heard in other products, that they actually utilize themselves for HMI and and SCADA graphics. That is that is our product. So you may have interacted it with us without even knowing it, and I hope we get to kind of talk more about things that we do. So before we jump into all the fun technical things as well, I kind of want to talk about just the overall software toolbox experience as we call it. We’re we’re more than just someone that wants to sell you a product. We we really do work with, the idea of solutions. How do we provide you value and solve the problems that you are facing as the person that’s actually working out there on the field, on those operation lines, and making things as well. And that’s really our big priority is providing a high level of knowledge, variety of the things we can work with, and then also the support. It’s very dear to me coming through the the support team is still working, you know, day to day throughout that software toolbox, and it’s something that has been ingrained into our heritage. Next year will be thirty years of software toolbox in 2026. So we’re established in 1996. Through those thirty years, we have committed to supporting the people that we work with. And I I I can just tell you that that entire motto lives throughout everyone that’s here. So from that, over 97% of the customers that we interact with through support say they had an awesome or great experience. Having someone that you can call that understands the products you’re working with, understands the environment you’re working in, understands the priority of certain things. If you ever have a plant shut down, we know how stressful that is. Those are things that we work through and help people throughout. So this really is the core pillars of Software Toolbox and who we are, beyond just the products, and and I really think this is something unique that we have continued to grow and stand upon for those thirty years. So jumping right into some of the industry challenges we’ve been seeing over the past few years. This is also a fun one for me, talking about data analytics and tying these things together. In my prior life and education, I worked with just tons of data, and I never fully knew where it might have come from, why it was such a mess, who structured it that way, but it’s my job to get some insights out of that. And knowing what the data actually was and why it matters is a big part of actually getting value. So if you have dirty data, if you have data that’s just clustered, it’s in silos, it’s very often you’re not gonna get much value out of it. This was a study that we found in 2024, from Garner Research, And it said that, based on the question that business were asked, were there any top strategic priorities for your data analytics functions in 2024? And almost 50%, it’s right at ’49, said that they wanted to improve data quality, and that was a strategic priority. This is about half the industry is just talking about data quality, and it’s exactly because of those reasons I said in my prior life gave me a headache, to look at all these different things that I don’t even know where they became from or or why they were so different. And the person that made that may have been gone may not have the contacts, and making that from the person that implemented things to the people that are making decisions, is a very big task sometimes. So if we can create a better pipeline of data quality at the beginning, makes those people’s lives a lot easier up front and allows them to get value out of that data a lot quicker. And that’s what businesses need. Shawn Tierney (Host): You know, I wanna just data quality. Right? Mhmm. I think a lot of us, when we think of that, we think of, you know, error error detection. We think of lost connections. We think of, you know, just garbage data coming through. But I I think from an analytical side, there’s a different view on that, you know, in line with what you were just saying. So how do you when you’re talking to somebody about data quality, how do you get them to shift gears and focus in on what you’re talking about and not like a quality connection to the device itself? Connor Mason (Guest): Absolutely. Yeah. We I kinda live in both those worlds now. You know, I I get to see that that connection state. And when you’re operating in real time, that quality is also very important to you. Mhmm. And I kind of use that at the same realm. Think of that when you’re thinking in real time, if you know what’s going on in the operation and where things are running, that’s important to you. That’s the quality that you’re looking for. You have to think beyond just real time. We’re talking about historical data. We’re talking about data that’s been stored for months and years. Think about the quality of that data once it’s made up to that level. Are they gonna understand what was happening around those periods? Are they gonna understand what those tags even are? Are they gonna understand what those conventions that you’ve implemented, to give them insights into this operation. Is that a clear picture? So, yeah, you’re absolutely right. There are two levels to this, and and that is a big part of it. The the real time data and historical, and we’re gonna get some of that into into our demo as well. It it’s a it’s a big area for the business, and the people working in the operations. Shawn Tierney (Host): Yeah. I think quality too. Think, you know, you may have data. It’s good data. It was collected correctly. You had a good connection to the device. You got it. You got it as often as you want. But that data could really be useless. It could tell you nothing. Connor Mason (Guest): Right. Exactly. Shawn Tierney (Host): Right? It could be a flow rate on part of the process that irrelevant to monitoring the actual production of the product or or whatever you’re making. And, you know, I’ve known a lot of people who filled up their databases, their historians, with they just they just logged everything. And it’s like a lot of that data was what I would call low quality because it’s low information value. Right? Absolutely. I’m sure you run into that too. Connor Mason (Guest): Yeah. We we run into a lot of people that, you know, I’ve got x amount of data points in my historian and, you know, then we start digging into, well, I wanna do something with it or wanna migrate. Okay. Like, well, what do you wanna achieve at the end of this? Right? And and asking those questions, you know, it’s great that you have all these things historized. Are you using it? Do you have the right things historized? Are they even set up to be, you know, worked upon once they are historized by someone outside of this this landscape? And I think OT plays such a big role in this, and that’s why we start to see the convergence of the IT and OT teams just because that communication needs to occur sooner. So we’re not just passing along, you know, low quality data, bad quality data as well. And we’ll get into some of that later on. So to jump into some of our products and solutions, I kinda wanna give this overview of the automation pyramid. This is where we work from things like the field device communications. And you you have certain sensors, meters, actuators along the actual lines, wherever you’re working. We work across all the industries, so this can vary between those. Through there, you work up kind of your control area. A lot of control engineers are working. This is where I think a lot of the audience is very familiar with PLCs. Your your typical name, Siemens, Rockwell, your Schneiders that are creating, these hardware products. They’re interacting with things on the operation level, and they’re generating data. That that was kind of our bread and butter for a very long time and still is that communication level of getting data from there, but now getting it up the stack further into the pyramid of your supervisory, MES connections, and it’ll also now open to these ERP. We have a lot of large corporations that have data across variety of different solutions and also want to integrate directly down into their operation levels. There’s a lot of value to doing that, but there’s also a lot of watch outs, and a lot of security concerns. So that’ll be a topic that we’ll be getting into. We also all know that the cloud is here. It’s been here, and it’s it’s gonna continue to push its way into, these cloud providers into OT as well. There there’s a lot of benefit to it, but there there’s also some watch outs as this kind of realm, changes in the landscape that we’ve been used to. So there’s a lot of times that we wanna get data out there. There’s value into AI agents. It’s a hot it’s a hot commodity right now. Analytics as well. How do we get those things directly from shop floor, up into the cloud directly, and how do we do that securely? It’s things that we’ve been working on. We’ve had successful projects, continues to be an interest area and I don’t see it slowing down at all. Now, when we kind of begin this level at the bottom of connectivity, people mostly know us for our top server. This is our platform for industrial device connectivity. It’s a thing that’s talking to all those different PLCs in your plant, whether that’s brownfield or greenfield. We pretty much know that there’s never gonna be a plant that’s a single PLC manufacturer, that exists in one plant. There’s always gonna be something that’s slightly different. Definitely from Brownfield, things different engineers made different choices, things have been eminent, and you gotta keep running them. TopServe provides this single platform to connect to a long laundry list of different PLCs. And if this sounds very familiar to Kepserver, well, you’re not wrong. Kepserver is the same exact technology that TopServer is. What’s the difference then is probably the biggest question we usually get. The difference technology wise is nothing. The difference in the back end is that actually it’s all the same product, same product releases, same price, but we have been the biggest single source of Kepserver or Topsyra implementation into the market, for almost two plus decades at this point. So the single biggest purchase that we own this own labeled version of Kepserver to provide to our customers. They interact with our support team, our solutions teams as well, and we sell it along the stack of other things because it it fits so well. And we’ve been doing this since the early two thousands when, Kepware was a a much smaller company than it is now, and we’ve had a really great relationship with them. So if you’ve enjoyed the technology of of Kepserver, maybe there’s some users out there. If you ever heard of TopServer and that has been unclear, I hope this clear clarifies it. But it it is a great technology stack that that we build upon and we’ll get into some of that in our demo. Now the other question is, what if you don’t have a standard communication protocol, like a modbus, like an Allen Bradley PLC as well? We see this a lot with, you know, testing areas, pharmaceuticals, maybe also in packaging, barcode scanners, weigh scales, printers online as well. They they may have some form of basic communications that talks over just TCP or or serial. And how do you get that information that’s really valuable still, but it’s not going through a PLC. It’s not going into your typical agent mind SCADA. It might be very manual process for a lot of these test systems as well, how they’re collecting and analyzing the data. Well, you may have heard of our Arm server as well. It’s been around, like I said, for a couple decades and just a proven solution that without coding, you can go in and build a custom protocol that expects a format from that device, translates it, puts it into standard tags, and now that those tags can be accessible through the open standards of OPC, or to it was a a Veeva user suite link as well. And that really provides a nice combination of your standard communications and also these more custom communications may have been done through scripting in the past. Well, you know, put this onto, an actual server that can communicate through those protocols natively, and just get that data into those SCADA systems, HMIs, where you need it. Shawn Tierney (Host): You know, I used that. Many years ago, I had an integrator who came to me. He’s like, Shawn, I wanna this is back in the RSVUE days. He’s like, Shawn, I I got, like, 20 Euotherm devices on a four eighty five, and they speak ASCII, and I gotta I gotta get into RSVUE 32. And, you know, OmniSIR, I love that you could you could basically developing and we did Omega and some other devices too. You’re developing your own protocol, but it’s beautiful. And and the fact that when you’re testing it, it color codes everything. So you know, hey. That part worked. The header worked. The data worked. Oh, the trailing didn’t work, or the terminated didn’t work, or the data’s not in the right format. Or I just it was a joy to work with back then, and I can imagine it’s only gotten better since. Connor Mason (Guest): Yeah. I think it’s like a little engineer playground where you get in there. It started really decoding and seeing how these devices communicate. And then once you’ve got it running, it it’s one of those things that it it just performs and, is saved by many people from developing custom code, having to manage that custom code and integrations, you know, for for many years. So it it’s one of those things that’s kinda tried, tested, and, it it’s kind of a staple still our our base level communications. Alright. So moving along kind of our automation pyramid as well. Another part of our large offering is the Cogent data hub. Some people may have heard from this as well. It’s been around for a good while. It’s been part of our portfolio for for a while as well. This starts building upon where we had the communication now up to those higher echelons of the pyramid. This is gonna bring in a lot of different connectivities. You if you’re not if you’re listening, it it’s kind of this cog and spoke type of concept for real time data. We also have historical implementations. You can connect through a variety of different things. OPC, both the profiles for alarms and events, and even OPC UA’s alarming conditions, which is still getting adoption across the, across the industry, but it is growing. As part of the OPC UA standard, we have integrations to MQTT. It can be its own MQTT broker, and it can also be an MQTT client. That has grown a lot. It’s one of those things that lives be besides OPC UA, not exactly a replacement. If you ever have any questions about that, it’s definitely a topic I love to talk about. There’s space for for this to combine the benefits of both of these, and it’s so versatile and flexible for these different type of implementations. On top of that, it it’s it’s a really strong tool for conversion and aggregation. You kind of add this, like, its name says, it’s a it’s a data hub. You send all the different information to this. It stores it into, a hierarchy with a variety of different modeling that you can do within it. That’s gonna store these values across a standard data format. Once I had data into this, any of those different connections, I can then send data back out. So if I have anything that I know is coming in through a certain plug in like OPC, bring that in, send it out to on these other ones, OPC, DA over to MQTT. It could even do DDA if I’m still using that, which I probably wouldn’t suggest. But overall, there’s a lot of good benefits from having something that can also be a standardization, between all your different connections. I have a lot of different things, maybe variety of OPC servers, legacy or newer. Bring that into a data hub, and then all your other connections, your historians, your MAS, your SCADAs, it can connect to that single point. So it’s all getting the same data model and values from a single source rather than going out and making many to many connections. A a large thing that it was originally, used for was getting around DCOM. That word is, you know, it might send some shivers down people’s spines still, to this day, but it’s it’s not a fun thing to deal with DCOM and also with the security hardening. It’s just not something that you really want to do. I’m sure there’s a lot of security professionals would advise against EPRA doing it. This tunneling will allow you to have a data hub that locally talks to any of the DA server client, communicate between two data hubs over a tunnel that pushes the data just over TCP, takes away all the comm wrappers, and now you just have values that get streamed in between. Now you don’t have to configure any DCOM at all, and it’s all local. So a lot of people went transitioning, between products where maybe the server only supports OPC DA, and then the client is now supporting OPC UA. They can’t change it yet. This has allowed them to implement a solution quickly and cost and at a cost effective price, without ripping everything out. Shawn Tierney (Host): You know, I wanna ask you too. I can see because this thing is it’s a data hub. So if you’re watching and you’re if you’re listening and not watching, you you’re not gonna see, you know, server, client, UAD, a broker, server, client. You know, just all these different things up here on the site. Do you what how does somebody find out if it does what they need? I mean, do you guys have a line they can call to say, I wanna do this to this. Is that something Data Hub can do, or is there a demo? What would you recommend to somebody? Connor Mason (Guest): Absolutely. Reach out to us. We we have a a lot of content outline, and it’s not behind any paywall or sign in links even. You you can always go to our website. It’s just softwaretoolbox.com. Mhmm. And that’s gonna get you to our product pages. You can download any product directly from there. They have demo timers. So typically with, with coaching data hub, after an hour, it will stop. You can just rerun it. And then call our team. Yeah. We have a solutions team that can work with you on, hey. What do I need as well? Then our support team, if you run into any issues, can help you troubleshoot that as well. So, I’ll have some contact information at the end, that’ll get some people to, you know, where they need to go. But you’re absolutely right, Shawn. Because this is so versatile, everyone’s use case of it is usually something a little bit different. And the best people to come talk to that is us because we’ve we’ve seen all those differences. So Shawn Tierney (Host): I think a lot of people run into the fact, like, they have a problem. Maybe it’s the one you said where they have the OPC UA and it needs to connect to an OPC DA client. And, you know, and a lot of times, they’re they’re a little gunshot to buy a license because they wanna make sure it’s gonna do exactly what they need first. And I think that’s where having your people can, you know, answer their questions saying, yes. We can do that or, no. We can’t do that. Or, you know, a a demo that they could download and run for an hour at a time to actually do a proof of concept for the boss who’s gonna sign off on purchasing this. And then the other thing is too, a lot of products like this have options. And you wanna make sure you’re buying the ticking the right boxes when you buy your license because you don’t wanna buy something you’re not gonna use. You wanna buy the exact pieces you need. So I highly recommend I mean, this product just does like, I have, in my mind, like, five things I wanna ask right now, but not gonna. But, yeah, def definitely, when it when it comes to a product like this, great to touch base with these folks. They’re super friendly and helpful, and, they’ll they’ll put you in the right direction. Connor Mason (Guest): Yeah. I I can tell you that’s working someone to support. Selling someone a solution that doesn’t work is not something I’ve been doing. Bad day. Right. Exactly. Yeah. And we work very closely, between anyone that’s looking at products. You know, me being as technical product managers, well, I I’m engaged in those conversations. And Mhmm. Yeah. If you need a demo license, reach out to us to extend that. We wanna make sure that you are buying something that provides you value. Now kind of moving on into a similar realm. This is one of our still somewhat newer offerings, I say, but we’ve been around five five plus years, and it’s really grown. And I kinda said here, it’s called OPC router, and and it’s not it’s not a networking tool. A lot of people may may kinda get that. It’s more of a, kind of a term about, again, all these different type of connections. How do you route them to different ways? It it kind of it it separates itself from the Cogent data hub, and and acting at this base level of being like a visual workflow that you can assign various tasks to. So if I have certain events that occur, I may wanna do some processing on that before I just send data along, where the data hub is really working in between converting, streaming data, real time connections. This gives you a a kind of a playground to work around of if I have certain tasks that are occurring, maybe through a database that I wanna trigger off of a certain value, based on my SCADA system, well, you can build that in in these different workflows to execute exactly what you need. Very, very flexible. Again, it has all these different type of connections. The very unique ones that have also grown into kind of that OT IT convergence, is it can be a REST API server and client as well. So I can be sending out requests to, RESTful servers where we’re seeing that hosted in a lot of new applications. I wanna get data out of them. Or once I have consumed a variety of data, I can become the REST server in OPC router and offer that to other applications to request data from itself. So, again, it can kind of be that centralized area of information. The other thing as we talked about in the automation pyramid is it has connections directly into SAP and ERP systems. So if you have work orders, if you have materials, that you wanna continue to track and maybe trigger things based off information from your your operation floors via PLCs tracking, how they’re using things along the line, and that needs to match up with what the SAP system has for, the amount of materials you have. This can be that bridge. It’s really is built off the mindset of the OT world as well. So we kinda say this helps empower the OT level because we’re now giving them the tools to that they understand what what’s occurring in their operations. And what could you do by having a tool like this to allow you to kind of create automated workflows based off certain values and certain events and automate some of these things that you may be doing manually or doing very convoluted through a variety of solutions. So this is one of those prod, products as well that’s very advanced in the things that supports. Linux and Docker containers is, is definitely could be a hot topic, rightly fleet rightfully so. And this can run on a on a Docker container deployed as well. So we we’ve seen that with the I IT folks that really enjoy being able to control and to higher deployment, allows you to update easily, allows you to control and spin up new containers as well. This gives you a lot of flexibility to to deploy and manage these systems. Shawn Tierney (Host): You know, I may wanna have you back on to talk about this. I used to there’s an old product called Rascal that I used to use. It was a transaction manager, and it would based on data changing or on a time that as a trigger, it could take data either from the PLC to the database or from the database to the PLC, and it would work with stored procedures. And and this seems like it hits all those points, And it sounds like it’s a visual like you said, right there on the slide, visual workflow builder. Connor Mason (Guest): Yep. Shawn Tierney (Host): So you really piqued my interest with this one, and and it may be something we wanna come back to and and revisit in the future, because, it just it’s just I know that that older product was very useful and, you know, it really solved a lot of old applications back in the day. Connor Mason (Guest): Yeah. Absolutely. And this this just takes that on and builds even more. If you if anyone was, kind of listening at the beginning of this year or two, a conference called Prove It that was very big in the industry, we were there to and we presented on stage a solution that we had. Highly recommend going searching for that. It’s on our web pages. It’s also on their YouTube links, and it’s it’s called Prove It. And OPC router was a big part of that in the back end. I would love to dive in and show you the really unique things. Kind of as a quick overview, we’re able to use Google AI vision to take camera data and detect if someone was wearing a hard hat. All that logic and behind of getting that information to Google AI vision, was through REST with OPC router. Then we were parsing that information back through that, connection and then providing it back to the PLCs. So we go all the way from a camera to a PLC controlling a light stack, up to Google AI vision through OPC router, all on hotel Wi Fi. It’s very imp it’s very, very fun presentation, and, our I think our team did a really great job. So a a a pretty new offering I have I wanna highlight, is our is our data caster. This is a an actual piece of hardware. You know, our software toolbox is we we do have some hardware as well. It’s just, part of the nature of this environment of how we mesh in between things. But the the idea is that, there’s a lot of different use cases for HMI and SCADA. They have grown so much from what they used to be, and they’re very core part of the automation stack. Now a lot of times, these are doing so many things beyond that as well. What we found is that in different areas of operations, you may not need all that different control. You may not even have the space to make up a whole workstation for that as well. What this does, the data caster, is, just simply plug it plugs it into any network and into an HDMI compatible display, and it gives you a very easy configure workplace to put a few key metrics onto a screen. So if I have different things from you can connect directly to PLCs like Allen Bradley. You can connect to SQL databases. You can also connect to rest APIs to gather the data from these different sources and build a a a kind of easy to to view, KPI dashboard in a way. So if you’re on a operation line and you wanna look at your current run rate, maybe you have certain things in the POC tags, you know, flow and pressure that’s very important for those operators to see. They may not be, even the capacity to be interacting with anything. They just need visualizations of what’s going on. This product can just be installed, you know, industrial areas with, with any type of display that you can easily access and and give them something that they can easily look at. It’s configured all through a web browser to display what you want. You can put on different colors based on levels of values as well. And it’s just I feel like a very simple thing that sometimes it seems so simple, but those might be the things that provide value on the actual operation floor. This is, for anyone that’s watching, kind of a quick view of a very simple screen. What we’re showing here is what it would look like from all the different data sources. So talking directly to ControlLogs PLC, talking to SQL databases, micro eight eight hundreds, an arrest client, and and what’s coming very soon, definitely by the end of this year, is OPC UA support. So any OPC UA server that’s out there that’s already having your PLC data or etcetera, this could also connect to that and get values from there. Shawn Tierney (Host): Can I can you make it I’m I’m here I go? Can you make it so it, like, changes, like, pages every few seconds? Connor Mason (Guest): Right now, it is a single page, but this is, like I said, very new product, so we’re taking any feedback. If, yeah, if there’s this type of slideshow cycle that would be, you know, valuable to anyone out there, let us know. We’re definitely always interested to see the people that are actually working out at these operation sites, what what’s valuable to them. Yeah. Shawn Tierney (Host): A lot of kiosks you see when when you’re traveling, it’ll say, like, line one well, I’ll just throw out there. Line one, and that’ll be on there for five seconds, and then it’ll go line two. That’ll be on there for five seconds, and then line you know, I and that’s why I just mentioned that because I can see that being a question that, that that I would get from somebody who is asking me about it. Connor Mason (Guest): Oh, great question. Appreciate it. Alright. So now we’re gonna set time for a little hands on demo. For anyone that’s just listening, we’re gonna I’m gonna talk about this at at a high level and walk through everything. But the idea is that, we have a few different POCs, very common in Allen Bradley and just a a Siemens seven, s seven fifteen hundred that’s in our office, pretty close to me on the other side of the wall wall, actually. We’re gonna first start by connecting that to our top server like we talked about. This is our industrial communication server, that offers both OCDA, OC UA, SweetLink connectivity as well. And then we’re gonna bring this into our Cogent data hub. This we talked about is getting those values up to these higher levels. What we’ll be doing is also tunneling the data. We talked about being able to share data through the data hubs themselves. Kinda explain why we’re doing that here and the value you can add. And then we’re also gonna showcase adding on MQTT to this level. Taking beta now just from these two PLCs that are sitting on a rack, and I can automatically make all that information available in the MQTT broker. So any MQTT client that’s out there that wants to subscribe to that data, now has that accessible. And I’ve created this all through a a really simple workflow. We also have some databases connected. Influx, we install with Code and DataHub, has a free visualization tool that kinda just helps you see what’s going on in your processes. I wanna showcase a little bit of that as well. Alright. So now jumping into our demo, when we first start off here is the our top server. Like I mentioned before, if anyone has worked with KEP server in the past, this is gonna look very similar. Like it because it is. The same technology and all the things here. The the first things that I wanted to establish in our demo, was our connection to our POCs. I have a few here. We’re only gonna use the Allen Bradley and the Siemens, for the the time that we have on our demo here. But how this builds out as a platform is you create these different channels and the devices connections between them. This is gonna be your your physical connections to them. It’s either, IP TCPIP connection or maybe your serial connection as well. We have support for all of them. It really is a long list. Anyone watching out there, you can kind of see all the different drivers that that we offer. So allowing this into a single platform, you can have all your connectivity based here. All those different connections that you now have that up the stack, your SCADA, your historians, MAS even as well, they can all go to a single source. Makes that management, troubleshooting, all those a bit easier as well. So one of the first things I did here, I have this built out, but I’ll kinda walk through what you would typically do. You have your Allen Bradley ControlLogix Ethernet driver here first. You know, I have some IPs in here I won’t show, but, regardless, we have our our our drivers here, and then we have a set of tags. These are all the global tags in the programming of the PLC. How I got these to to kind of map automatically is in our in our driver, we’re able to create tags automatically. So you’re able to send a command to that device and ask for its entire tag database. They can come back, provide all that, map it out for you, create those tags as well. This saves a lot of time from, you know, an engineer have to go in and, addressing all the individual items themselves. So once it’s defined in the program project, you’re able to bring this all in automatically. I’ll show now how easy that makes it connecting to something like the Cogent data hub. In a very similar fashion, we have a connection over here to the Siemens, PLC that I also have. You can see beneath it all these different tag structures, and this was created the exact same way. While those those PLC support it, you can do an automatic tag generation, bring in all the structure that you’ve already built out your PLC programming, and and make this available on this OPC server now as well. So that’s really the basis. We first need to establish communications to these PLCs, get that tag data, and now what do we wanna do with it? So in this demo, what I wanted to bring up was, the code in DataHub next. So here, I see a very similar kind of layout. We have a different set set of plugins on the left side. So for anyone listening, the Cogent Data Hub again is kind of our aggregation and conversion tool. All these different type of protocols like OPC UA, OPC DA, and OPC A and E for alarms and events. We also support OPC alarms and conditions, which is the newer profile for alarms in OPC UA. We have all a variety of different ways that you can get data out of things and data’s into the data hub. We can also do bridging. This concept is, how you share data in between different points. So let’s say I had a connection to one OPC server, and it was communicating to a certain PLC, and there were certain registers I was getting data from. Well, now I also wanna connect to a different OPC server that has, entirely different brand of PLCs. And then maybe I wanna share data in between them directly. Well, with this software, I can just bridge those points between them. Once they’re in the data hub, I can do kind of whatever I want with them. I can then allow them to write between those PLCs and share data that way, and you’re not now having to do any type of hardwiring directly in between them, and then I’m compatible to communicate to each other. Through the standards of OPC and these variety of different communication levels, I can integrate them together. Shawn Tierney (Host): You know, you bring up a good point. When you do something like that, is there any heartbeat? Like, is there on the general or under under, one of these, topics? Is there are there tags we can use that are from DataHub itself that can be sent to the destination, like a heartbeat or, you know, the merge transactions? Or Connor Mason (Guest): Yeah. Absolutely. So with this as well, there’s pretty strong scripting engine, and I have done that in the past where you can make internal tags. And that that could be a a timer. It could be a counter. And and just kind of allows you to create your own tags as well that you could do the same thing, could share that, through bridge connection to a PLC. So, yeah, there there are definitely some people that had those cert and, you know, use cases where they wanna get something to just track, on this software side and get it out to those hardware PLCs. Absolutely. Shawn Tierney (Host): I mean, when you send out the data out of the PLC, the PLC doesn’t care to take my data. But when you’re getting data into the PLC, you wanna make sure it’s updating and it’s fresh. And so, you know, they throw a counter in there, the script thing, and be able to have that. As as long as you see that incrementing, you know, you got good data coming in. That’s that’s a good feature. Connor Mason (Guest): Absolutely. You know, another big one is the the redundancy. So what this does is beyond just the OPC, we can make redundancy to basically anything that has two things running of it. So any of these different connections. How it’s unique is what it does is it just looks at the buckets of data that you create. So for an example, if I do have two different OPC servers and I put them into two areas of, let’s say, OPC server one and OPC server two, I can what now create an OPC redundancy data bucket. And now any client that connects externally to that and wants that data, it’s gonna go talk to that bucket of data. And that bucket of data is going to automatically change in between sources as things go down, things come back up, and the client would never know what’s hap what that happened unless you wanted to. There are internal tasks to show what’s the current source and things, but the idea is to make this trans kind of hidden that regardless of what’s going on in the operations, if I have this set up, I can have my external applications just reading from a single source without knowing that there’s two things behind it that are actually controlling that. Very important for, you know, historian connections where you wanna have a full complete picture of that data that’s coming in. If you’re able to make a redundant connection to two different, servers and then allow that historian to talk to a single point where it doesn’t have to control that switching back and forth. It it will just see that data flow streamlessly as as either one is up at that time. Kinda beyond that as well, there’s quite a few other different things in here. I don’t think we have time to cover all of them. But for for our demo, what I wanna focus on first is our OPC UA connection. This allows us both to act as a OPC UA client to get data from any servers out there, like our top server. And also we can act as an OPC UA server itself. So if anything’s coming in from maybe you have multiple connections to different servers, multiple connections to other things that aren’t OPC as well, I can now provide all this data automatically in my own namespace to allow things to connect to me as well. And that’s part of that aggregation feature, and kind of topic I was mentioning before. So with that, I have a connection here. It’s pulling data all from my top server. I have a few different tags from my Alec Bradley and and my Siemens PLC selected. The next part of this, while I was meshing, was the tunneling. Like I said, this is very popular to get around DCOM issues, but there’s a lot of reasons why you still may use this beyond just the headache of DCOM and what it was. What this runs on is a a TCP stream that takes all the data points as a value, a quality, and a timestamp, and it can mirror those in between another DataHub instance. So if I wanna get things across a network, like my OT side, where NASH previously, I would have to come in and allow a, open port onto my network for any OPC UA clients, across the network to access that, I can now actually change the direction of this and allow me to tunnel data out of my network without opening up any ports. This is really big for security. If anyone out there, security professional or working as an engineer, you have to work with your IT and security a lot, they don’t you don’t wanna have an open port, especially to your operations and OT side. So this allows you to change that direction of flow and push data out of this direction into another area like a DMZ computer or up to a business level computer as well. The other things as well that I have configured in this demo, the benefit of having that tunneling streaming data across this connection is I can also store this data locally in a, influx database. The purpose of that then is that I can actually historize this, provide then if this connection ever goes down to backfill any information that was lost during that tunnel connection going down. So with this added layer on and real time data scenarios like OPC UA, unless you have historical access, you would lose a lot of data if that connection ever went down. But with this, I can actually use the back end of this InfluxDB, buffer any values. When my connection comes back up, pass them along that stream again. And if I have anything that’s historically connected, like, another InfluxDB, maybe a PI historian, Vue historian, any historian offering out there that can allow that connection. I can then provide all those records that were originally missed and backfill that into those systems. So I switched over to a second machine. It’s gonna look very similar here as well. This also has an instance of the Cogent Data Hub running here. For anyone not watching, what we’ve actually have on this side is the the portion of the tunneler that’s sitting here and listening for any data requests coming in. So on my first machine, I was able to connect my PLCs, gather that information into Cogent DataHub, and now I’m pushing that information, across the network into a separate machine that’s sitting here and listening to gather information. So what I can quickly do is just make sure I have all my data here. So I have these different points, both from my Allen Bradley PLCs. I have a few, different simulation demo points, like temperature, pressure, tank level, a few statuses, and all this is updating directly through that stream as the PLC is updating it as well. I also have my scenes controller. I have some, current values and a few different counters tags as well. All of this again is being directly streamed through that tunnel. I’m not connecting to an OPC server at all on this side. I can show you that here. There’s no connections configured. I’m not talking to the PLCs directly on this machine as well. But maybe we’ll pass all the information through without opening up any ports on my OT demo machine per se. So what’s the benefit of that? Well, again, security. Also, the ability to do the store and forward mechanisms. On the other side, I was logging directly to a InfluxDB. This could be my d- my buffer, and then I was able to configure it where if any values were lost, to store that across the network. So now with this side, if I pull up Chronic Graph, which is a free visualization tool that installs with the DataHub as well, I can see some very nice, visual workflows and and visual diagrams of what is going on with this data. So I have a pressure that is just a simulator in this, Allen Bradley PLC that ramps up and and comes back down. It’s not actually connected to anything that’s reading a real pressure, but you can see over time, I can kind of change through these different layers of time. And I might go back a little far, but I have a lot of data that’s been stored in here. For a while during my test, I turned this off and, made it fail, but then I came back in and I was able to recreate all the data and backfill it as well. So through through these views, I can see that as data disconnects, as it comes back on, I have a very cyclical view of the data because it was able to recover and store and forward from that source. Like I said, Shawn, data quality is a big thing in this industry. It’s a big thing for people both at the operations side, and both people making decision in the business layer. So being able to have a full picture, without gaps, it is definitely something that, you should be prioritizing, when you can. Shawn Tierney (Host): Now what we’re seeing here is you’re using InfluxDB on this, destination PC or IT side PC and chronograph, which was that utility or that package that comes, gets installed. It’s free. But you don’t actually have to use that. You could have sent this in to an OSI pi or Exactly. Somebody else’s historian. Right? Can you name some of the historians you work with? I know OSI pie. Connor Mason (Guest): Yeah. Yeah. Absolutely. So there’s quite a few different ones. As far as what we support in the Data Hub natively, Amazon Kinesis, the cloud hosted historian that we can also do the same things from here as well. Aviva Historian, Aviva Insight, Apache Kafka. This is a a kind of a a newer one as well that used to be a very IT oriented solution, now getting into OT. It’s kind of a similar database structure where things are stored in different topics that we can stream to. On top of that, just regular old ODBC connections. That opens up a lot of different ways you can do it, or even, the old classic OPC, HDA. So if you have any, historians that that can act as an OPC HDA, connection, we we can also stream it through there. Shawn Tierney (Host): Excellent. That’s a great list. Connor Mason (Guest): The other thing I wanna show while we still have some time here is that MQTT component. This is really growing and, it’s gonna continue to be a part of the industrial automation technology stack and conversations moving forward, for streaming data, you know, from devices, edge devices, up into different layers, both now into the OT, and then maybe out to, IT, in our business levels as well, and definitely into the cloud as we’re seeing a lot of growth into it. Like I mentioned with Data Hub, the big benefit is I have all these different connections. I can consume all this data. Well, I can also act as an MQTT broker. And what what a broker typically does in MQTT is just route data and share data. It’s kind of that central point where things come to it to either say, hey. I’m giving you some new values. Share it with someone else. Or, hey. I need these values. Can you give me that? It really fits in super well with what this product is at its core. So all I have to do here is just enable it. What that now allows is I have an example, MQTT Explorer. If anyone has worked with MQTT, you’re probably familiar with this. There’s nothing else I configured beyond just enabling the broker. And you can see within this structure, I have all the same data that was in my Data Hub already. The same things I were collecting from my PLCs and top server. Now I’ve embedded these as MPPT points and now I have them in JSON format with the value, their timestamp. You can even see, like, a little trend here kind of matching what we saw in Influx. And and now this enables all those different cloud connectors that wanna speak this language to do it seamlessly. Shawn Tierney (Host): So you didn’t have to set up the PLCs a second time to do this? Nope. Connor Mason (Guest): Not at all. Shawn Tierney (Host): You just enabled this, and now the data’s going this way as well. Exactly. Connor Mason (Guest): Yeah. That’s a really strong point of the Cogent Data Hub is once you have everything into its structure and model, you just enable it to use any of these different connections. You can get really, really creative with these different things. Like we talked about with the the bridging aspect and getting into different systems, even writing down the PLCs. You can make crust, custom notifications and email alerts, based on any of these values. You could even take something like this MTT connection, tunnel it across to another data hub as well, maybe then convert it to OPC DA. And now you’ve made a a a new connection over to something that’s very legacy as well. Shawn Tierney (Host): Yeah. That, I mean, the options here are just pretty amazing, all the different things that can be done. Connor Mason (Guest): Absolutely. Well, I, you know, I wanna jump back into some of our presentation here while we still got the time. And now after we’re kinda done with our demo, there’s so many different ways that you can use these different tools. This is just a really simple, kind of view of the, something that used to be very simple, just connecting OpenSea servers to a variety of different connections, kind of expanding onto with that that’s store and forward, the local influx usage, getting out to things like MTT as well. But there’s a lot more you can do with these solutions. So like Shawn said, reach out to us. We’re happy to engage and see what we can help you with. I have a few other things before we wrap up. Just overall, it we’ve worked across nearly every industry. We have installations across the globe on all continents. And like I said, we’ve been around for pushing thirty years next year. So we’ve seen a lot of different things, and we really wanna talk to anyone out there that maybe has some struggles that are going on with just connectivity, or you have any ongoing projects. If you work in these different industries or if there’s nothing marked here and you have anything going on that you need help with, we’re very happy to sit down and let you know if there’s there’s something we can do there. Shawn Tierney (Host): Yeah. For those who are, listening, I mean, we see most of the big energy and consumer product, companies on that slide. So I’m not gonna read them off, but, it’s just a lot of car manufacturers. You know, these are these are these, the household name brands that everybody knows and loves. Connor Mason (Guest): So kind of wrap some things up here. We talked about all the different ways that we’ve kind of helped solve things in the past, but I wanna highlight some of the unique ones, that we’ve also gone do some, case studies on and and success stories. So this one I actually got to work on, within the last few years that, a plastic packaging, manufacturer was looking to track uptime and downtime across multiple different lines, and they had a new cloud solution that they were already evaluating. They’re really excited to get into play. They they had a lot of upside to, getting things connected to this and start using it. Well, what they had was a lot of different PLCs, a lot of different brands, different areas, different, you know, areas of operation that they need to connect to. So what they used was to first get that into our top server, kind of similar to how they showed them use in their in our demo. We just need to get all the data into a centralized platform first, get that data accessible. Then from there, once they had all that information into a centralized area, they used the Cogent Data Hub as well to help aggregate that information and transform it to be sent to the cloud through MQTT. So very similar to the demo here, this is actually a real use case of that. Getting information from PLCs, structuring it into that how that cloud system needed it for MQTT, and streamlining that data connection to now where it’s just running in operation. They constantly have updates about where their lines are in operation, tracking their downtime, tracking their uptime as well, and then being able to do some predictive analytics in that cloud solution based on their history. So this really enabled them to kind of build from what they had existing. It was doing a lot of manual tracking, into an entirely automated system with management able to see real views of what’s going on at this operation level. Another one I wanna talk about was we we were able to do this success story with, Ace Automation. They worked with a pharmaceutical company. Ace Automation is a SI and they were brought in and doing a lot of work with some some old DDE connections, doing some custom Excel macros, and we’re just having a hard time maintaining some legacy systems that were just a pain to deal with. They were working with these older files, from some old InTouch histor HMIs, and what they needed to do was get something that was not just based on Excel and doing custom macros. So one product we didn’t get to talk about yet, but we also carry is our LGH file inspector. It’s able to take these files, put them out into a standardized format like CSV, and also do a lot of that automation of when when should these files be queried? Should they be, queried for different lengths? Should they be output to different areas? Can I set these up in a scheduled task so it can be done automatically rather than someone having to sit down and do it manually in Excel? So they will able to, recover over fifty hours of engineering time with the solution from having to do late night calls to troubleshoot a, Excel macro that stopped working, from crashing machines, because they were running a legacy systems to still support some of the DDE servers, into saving them, you know, almost two hundred plus hours of productivity. Another example, if we’re able to work with a renewable, energy customer that’s doing a lot of innovative things across North America, They had a very ambitious plan to double their footprint in the next two years. And with that, they had to really look back at their assets and see where they currently stand, how do we make new standards to support us growing into what we want to be. So with this, they had a lot of different data sources currently. They’re all kind of siloed at the specific areas. Nothing was really connected commonly to a corporate level area of historization, or control and security. So again, they they were able to use our top server and put out a standard connectivity platform, bring in the DataHub as an aggregation tool. So each of these sites would have a top server that was individually collecting data from different devices, and then that was able to send it into a single DataHub. So now their corporate level had an entire view of all the information from these different plants in one single application. That then enabled them to connect their historian applications to that data hub and have a perfect view and make visualizations off of their entire operations. What this allowed them to do was grow without replacing everything. And that’s a big thing that we try to strive on is replacing and ripping out all your existing technologies. It’s not something you can do overnight. But how do we provide value and gain efficiency with what’s in place and providing newer technologies on top of that without disrupting the actual operation as well? So this was really, really successful. And at the end, I just wanna kind of provide some other contacts and information people can learn more. We have a blog that goes out every week on Thursdays. A lot of good technical content out there. A lot of recast of the the awesome things we get to do here, the success stories as well, and you can always find that at justblog.softwaretoolbox.com. And again, our main website is justsoftwaretoolbox.com. You can get product information, downloads, reach out to anyone on our team. Let’s discuss what what issues you have going on, any new projects, we’ll be happy to listen. Shawn Tierney (Host): Well, Connor, I wanna thank you very much for coming on the show and bringing us up to speed on not only software toolbox, but also to, you know, bring us up to speed on top server and doing that demo with top server and data hub. Really appreciate that. And, I think, you know, like you just said, if anybody, has any projects that you think these solutions may be able to solve, please give them a give them a call. And if you’ve already done something with them, leave a comment. You know? To leave a comment, no matter where you’re watching or listening to this, let us know what you did. What did you use? Like me, I used OmniServer all those many years ago, and, of course, Top Server as an OPC server. But if you guys have already used Software Toolbox and, of course, Symbol Factory, I use that all the time. But if you guys are using it, let us know in the comments. It’s always great to hear from people out there. I know, you know, with thousands of you guys listening every week, but I’d love to hear, you know, are you using these products? Or if you have questions, I’ll funnel them over to Connor if you put them in the comments. So with that, Connor, did you have anything else you wanted to cover before we close out today’s show? Connor Mason (Guest): I think that was it, Shawn. Thanks again for having us on. It was really fun. Shawn Tierney (Host): I hope you enjoyed that episode, and I wanna thank Connor for taking time out of his busy schedule to come on the show and bring us up to speed on software toolbox and their suite of products. Really appreciated that demo at the end too, so we actually got a look at if you’re watching. Gotta look at their products and how they work. And, just really appreciate them taking all of my questions. I also appreciate the fact that Software Toolbox sponsored this episode, meaning we were able to release it to you without any ads. So I really appreciate them. If you’re doing any business with Software Toolbox, please thank them for sponsoring this episode. And with that, I just wanna wish you all good health and happiness. And until next time, my friends, peace. Until next time, Peace ✌️  If you enjoyed this content, please give it a Like, and consider Sharing a link to it as that is the best way for us to grow our audience, which in turn allows us to produce more content

This week host James Weaver is joined by CEO Matt Manocherian and Alex Vigderman to break down a few 1-2 teams and if they can right the ship in the coming weeks. The Falcons, Texans, Ravens, and Chiefs all have flaws that need addressed, but some are more fixable than others.Can Michael Penix Jr. scrub the Panthers game from his head? Is the Texans offensive line permanently broken? How are offenses able to 'take flight' against the Ravens secondary? How can Patrick Mahomes get back to his MVP self?Also, we discuss the MVP market, the recent performance of Drake Maye, and some of the leaderboards on our DataHub.Off The Charts features a blend of statistical insights, tactical analysis, and personal opinions, aimed at providing listeners with a comprehensive understanding of the week's key matchups and the intricacies of the sport. You can follow our content on Twitter at @Football_SIS, on Bluesky at @sportsinfosis.bsky.social and at sportsinfosolutions.com.

Bhaskar Ghosh, Partner at 8VC, reflects on his journey from Calcutta to Silicon Valley, spanning influential roles at Oracle, Yahoo, LinkedIn, and NerdWallet before moving into venture capital. Now a leader at 8VC, BG introduces his “geometry framework” (persona, product, budget) for enterprise startups, shares insights on the opportunities in generative AI and data infrastructure, and talks about why managing uncertainty is the core skill in zero-to-one journeys. He also emphasizes intentional networking, the long-term nature of venture relationships, and his deep passion for music through his support for Ragas Live.In this episode, you'll learn:[01:56] BG's early journey from Calcutta to Silicon Valley and his career in academia, Yahoo, Oracle, LinkedIn, and NerdWallet[06:10] Why he calls himself a “secondhand entrepreneur” and what excites him most about venture capital[11:22] 8VC's focus areas and why incubation is core to the firm's strategy[14:05] The “geometry framework” for evaluating enterprise startups: persona, product, budget[19:30] Where BG sees opportunity in generative AI: orchestration, knowledge graphs, semantic layers, observability[25:12] Why networking must be intentional and based on service, not transactions[28:34] BG's advice to founders on standing out and building authentic investor relationshipsThe non-profit Bhaskar is passionate about:  SACSA (Society for Arts and Culture of South Asia)About Bhaskar GhoshBhaskar Ghosh (BG) is a Partner at 8VC, where he leads investments in enterprise software, AI, data infrastructure, fintech, and healthcare, while incubating multiple startups. Previously, he held senior roles at Oracle and Yahoo, was the founding head of data infrastructure at LinkedIn, and served as CTO at NerdWallet, helping scale it to IPO. BG holds a PhD in Computer Science from Yale and is passionate about helping founders navigate zero-to-one journeys. Outside venture, he is deeply engaged in Indian classical music and supports community initiatives like Ragas Live.About 8VC8VC is a venture capital firm with approximately $7B in assets under management, investing in transformative technologies across enterprise software, AI, healthcare, logistics, fintech, and defense. With offices in Austin and San Francisco, 8VC partners with early-stage founders and also dedicates significant capital to incubation—building new companies alongside entrepreneurs. Its mission is to back ambitious founders solving global problems with scalable, science-driven solutions. 8VC's portfolio includes category-defining startups that are shaping industries and tackling global challenges, including DataHub, Yugabyte, LightBeam, Tezi, OpenGov, Nile, AI21 Labs, AMP, Bedrock Robotics, 180° Insurance, Cambium, Candid Health among others.Subscribe to our podcast and stay tuned for our next episode.

Episode SummaryIn this episode of OnBase, host Chris Moody sits down with Lydia Hutchison for a powerful conversation on what works in modern B2B prospecting. Lydia explains why typical AI-personalized messages fail to cut through and how relevance, rooted in deep customer understanding, wins every time.She unpacks her triple-touch framework, the value of tone and timing, and the human psychology that underpins effective outreach. Lydia also reveals her favorite high-converting tactic that combines manual research with real-time relevance. If you're struggling with connect rates, sequence performance, or objection handling, this episode offers a fresh, actionable perspective.Key TakeawaysRelevance Trumps Personalization: Generic personalization wastes the prospect's time. Relevance speaks directly to their daily pain and success metrics—and that's what drives replies.Triple-Touch Strategy Works: Lydia advocates a three-channel approach—phone, LinkedIn, email—for testing message resonance and adjusting in real-time based on feedback.Lead with Psychology, Not Scripts: Authentic, thoughtful outreach begins with understanding how people accomplish their tasks—and how you can help them do it more effectively.Objections Aren't Always Real: Recognize the difference between a true objection and simple disinterest. Learn to use tone, timing, and multichannel follow-up to stay human and helpful.AI is a Research Assistant, Not a Salesperson: When used well, AI can support better outreach by helping reps research personas and challenges, but it shouldn't write your messages for you.Quotes“Everybody is getting their job done without you. So your job is to show them how to do it better—not tell them they're doing it wrong.”Best Moments (0:56) Lydia Hutchison's Journey into Sales (2:59)Developing Expertise in Sales Execution and Prospecting  (8:00) Differentiating Relevance and Personalization in Prospecting(12:09) Key Factors to Make a Sales Message Stand Out (14:19) Example of Focusing on Relevance Over Personalization (16:27) Process for Ensuring Consistent and Compelling Messaging Across Sales Teams(18:34) Approaching Objection Handling (20:33) Actionable Advice for Struggling Prospecting Teams Shout-outsJason Bay – Lydia recommends Jason for practical advice on sales openers and messaging, especially for go-to-market teams. His content helps reps connect more effectively with prospects.Jen Allen-Knuth- Jen's focus on the psychology of sales resonates with Lydia. She recommends Jen's insightful LinkedIn posts on buyer behavior and objection handling.About the GuestLydia Hutchison is the Head of Business Development at DataHub. She is a data-obsessed sales leader, builder of outbound sales motions, from early-stage startups to global enterprises. Lydia is passionate about coaching for success and empowering sales development orgs to crush their revenue and career goals.Website: datahub.comConnect with Lydia.

Check out my interview with Shirshanka Das, CTO and Co-founder of Acryl Data, at the Snowflake Summit. We discussed some interesting topics, including DataHub, Acryl, and the Control Plane for Data and AI. -- An important part of our discussion centered around the concept of a "Control Plane for Data and AI" -- As AI use-cases become more prevalent, a Control Plane serves as a crucial tool for organizations. It offers a single point of control and visibility for all data and AI operations, simplifying the complexities of AI implementation -- We also discussed about the future of AI use-cases given the hype of metadata solutions on the market -- On the subject of open source, Shirshanka emphasized its importance in fostering a collaborative environment for knowledge sharing and innovation Stay tuned for more insights and stories from the Snowflake Summit! #data #ai #snowflakesummit #snowflakeflake2024 #acryldata #theravitshow

Shirshanka Das (@shirshanka) is the CTO of Acryl Data and founder of DataHub, which bills itself as the #1 open-source metadata platform. It enables data discovery, data observability and federated governance to help tame complex data ecosystems. Shirshanka first developed DataHub while at LinkedIn, but has grown it into an independent project with a thriving community. Contributor is looking for a community manager! If you want to know more, shoot us an email at eric@scalevp.com. Subscribe to Contributor on Substack for email notifications! In this episode we discuss: How DataHub differs from traditional data catalogs Themes around why community members get involved and stick with the project Partnering with Netflix to develop runtime metadata model extensibility The influence of the pandemic on DataHub's open-sourcing Dealing with the future of a project with big community and unlimited scope Links: DataHub The History of DataHub

David Hows catches up with Jon Bilger to talk about a long list of innovations and new features at PredictWind. As an Olympic and America's Cup sailor, Jon is one of the sailing world's, cool geeks. Very few people have competed at the level Jon has, and possess the ability to turn their knowledge into tech tools that any sailor can use. PredictWind is the global leader in weather forecasting for sailors and its used by both top racers and everyday cruisers alike. As a user of PredictWind for almost a decade, I have found it perfect for my departure planning and weather routing at sea. Having crossed the Tasman 18-times and sailed to increasingly higher latitudes, having good forecasts helps me stay out of trouble. The advent of faster download speeds with Iridium Go Exec and Starlink, along with the new PredictWind Data Hub has made PredictWind even more valuable to use. I don't normally plug products, but this technology is must have for safety, so here are some extra resources to help you research it further; Features Weather Routing - https://www.predictwind.com/features/weather-routing Departure Planning - https://www.predictwind.com/features/departure-planning AIS Data - https://www.predictwind.com/features/ais-data GPS tracking - https://www.predictwind.com/gps-tracking   Products Iridium GO - https://www.predictwind.com/iridium-go Iridium GO exec - https://www.predictwind.com/iridium-go-exec Starlink - https://www.predictwind.com/starlink DataHub - https://www.predictwind.com/datahub

4GLOBAL #4GBL are the experts in Major Sports Events and big data insights. They apply proprietary data and technology to enable clients to maximise health and social benefits derived from physical activity. Their expertise include: - Advice and assistance on the hosting Major Sports Events - KPI actualisation, including driving participation in sport. - Provision of new insights derived from big data Their DataHub is the largest repository for sports and leisure data globally. Integrated and enhanced through a suite of business intelligence modules, the DataHub can be accessed globally via an online portal. At 55p they have a market capitalisation of £14m, generated topline revenue growth of 53% from 2022 - 2023, and are forecast to generate 20% growth each year from 2023 - 2025. Their broker Canaccord Genuity have a 12 month target of 100p and state: “On a CY24E EV/Sales of 1.7x, 4GLOBAL trades at a >50% discount to UK-listed data/intelligence peers, despite its strong organic growth, improving revenue visibility and profitable financial profile”

Skip the Queue is brought to you by Rubber Cheese, a digital agency that builds remarkable systems and websites for attractions that helps them increase their visitor numbers. Your host is  Kelly Molson, Founder of Rubber Cheese.Download the Rubber Cheese 2023 Visitor Attraction Website Report - the annual benchmark statistics for the attractions sector.If you like what you hear, you can subscribe on iTunes, Spotify, and all the usual channels by searching Skip the Queue or visit our website rubbercheese.com/podcast.If you've enjoyed this podcast, please leave us a five star review, it really helps others find us. And remember to follow us on Twitter for your chance to win the books that have been mentioned in this podcastCompetition ends on 29th March 2024. The winner will be contacted via Twitter.  Show references: David Green | LinkedInhttps://www.blenheimpalace.com/Head of Innovation at Blenheim PalaceDavid Green is responsible for driving innovation at Blenheim to deliver value from the implementation of novel business methods and new concepts. His role involves building a culture of continual improvement and innovation, bringing together and contextualising novel datasets through a data and IoT network infrastructure, and identifying opportunities to enhance customer experiences.David leads the research and development at Blenheim, cultivating university partnerships, that helps fuse specialised knowledge with Blenheim's diverse landscape and practical challenges. Moreover, he initiated the Innovation and Continual Improvement network, fostering collaboration among sector leads to share expertise and address common challenges. Joseph Paul | LinkedInhttps://vennersys.co.uk/Associate Director – Key Account ManagerWith 10 years of experience in SaaS Account Management and 6 years at Vennersys, Joe works closely with visitor attractions to optimise system performance and internal processes. He acts as a conduit between attraction managers and Vennersys, helping facilitate constructive communication to further develop and improve Vennersys' own services based on customer needs or industry trends.In his personal life, Joe can either be found playing hockey for his local club or taking long, refreshing walks in the hills and fields near his home. Transcriptions:  Kelly Molson: Welcome to Skip The Queue, a podcast for people working in or working with visitor attractions. I'm your host, Kelly Molson. On today's episode I speak with David Green, Head of Innovation at Blenheim Palace and Joseph Paul, Associate Director - Key Account Manager at Vennersys.We're talking about data - but not just the importance of it (we all know that right?). David and Joe share the exciting data and AI reporting systems that Blenheim have created, allowing them to predict, and not just report on past performance. This is a really interesting episode and if you're been a little bit put off or a little bit scared about AI up until this point, this might be the episode that changes your mind.If you like what you hear, you can subscribe on all the usual channels by searching Skip The Queue. Kelly Molson: David, Joe, it is lovely to have you both on the podcast today. Thank you for joining me on Skip the Queue. David Green: It's great to be here. Joseph Paul: Thanks for having us. Kelly Molson: That sounded very positive, guys. Thanks. Feel the enthusiasm. David Green: Let's see how the first question goes, shall we? Kelly Molson: Listen, everyone worries about these icebreaker questions. It's just we're just in a pub, in a coffee shop having a little chat. That's all it is. Right, I want to know. We'll start with you, Joe. What was the last thing you binge watched on your streaming service of choice? Joseph Paul: Gosh, that's a very good question. The last series we binge watch was a series called Bodies on Netflix, which is about a murder that happens in four different time periods and four detectives are trying to solve the murder. Very good if you haven't watched it.  Kelly Molson: I have seen this and Joe, it hurt my head a little bit.Joseph Paul: Yeah. It is hard to keep track of some of the plots through the different times, but there's a very good ending worth watching if you haven't, David? David Green:  I don't think I have. I didn't get a chance to watch TV. Kelly Molson: So same question to you, David. That's a really good series as well, Joe. I thoroughly enjoyed that, although it did hurt the backwards forwards bit a little bit, was a bit mind blowing. Same question to you, David. What was the last thing that you binge watched? David Green: Well, the last thing I probably binge watched was probably Breaking Bad. That just sort of shows you how long ago it was. I binge watched anything, but I'm desperate to watch it again. It was so good. I was just hooked on the first episode. I just loved every single minute of that. Kelly Molson: Have you seen that, Joe? Joseph Paul: Yes. Very good series. Probably one of the best of all time. And the question back would be, have you watched Better Call Saul? David Green: Yeah, but I didn't find it as good. I say I didn't find as good. It was still great. I'm very fussy in the Greenhouse song. Kelly Molson: I feel like I'm the only person in the whole world who's not watched Breaking Bad, which is this is quite controversial, isn't it? Everybody says that I would love it and I should watch it, but I feel overwhelmed that there's so many series to it and it would take up all of my TV viewing time for months and months. It would be the only thing that I could probably watch for the entire year and that feels too much. Joseph Paul: It's well worth it. Absolutely. You should do it.Kelly Molson: Dedicate 2024 as the year for Breaking Bad. David Green: I'm going to own up. I've not watched a single episode of The Crown either and some of it was filmed at Blenheim. So I'm really embarrassed to admit that on this podcast.Kelly Molson: That is a statement in a half, David. See, this is why I do the icebreakers. You never know what dirt you're going to get out. David, we're going to start with you with this one. What is the one food or drink that you cannot eat and you can't even think about without feeling a little bit queasy? David Green: That's cheese pastry straight away. I remember when I was at school, we had a home economics club. I remember making these cheese straws and I took them home and I was so environmentally ill after these cheese straws ever since, I just can't even look at cheese pastry. All these nibbles that people without for drinks can't bear it. Cheese and pastry together is wrong. Kelly Molson: This is really sad. I love a little cheese straw. I feel sad for you that you can't eat a cheese straw, David. I feel sad for you. Joe, what about you? Joseph Paul: I can pretty much eat anything and I'm not overly put off by much. I think the one thing that turns me away from food is horseradish and any sauce. That's probably my only sort of food that I won't go to and puts me off eating anything that has.Kelly Molson: Just horseradish or sauce in general. Are we talking like, sweet chilli dip? No?Joseph Paul: Just horseradish. So anything that has that in it, I will stay away from. But apart from that, I'll pretty much eat anything anyone puts on my plate. David Green: I think you're missing out, Joe. Kelly Molson: Do you know what's probably really nice as well? Is a cheese straw with horseradish.Joseph Paul: But cheese straws are the best. David Green: I'm going to have to leave the room in a minute. We could talk about cheese straw. Kelly Molson: Sorry. All right, let's move on from that. Right, I want to know I was quite kind to those ones. I want to know what your unpopular opinions are. Joe, let's start with you. Joseph Paul: Not sure this is going to go down too well, but my unpopular opinion is Harry Potter is an overrated film series. Kelly Molson: Books or films or both? Joseph Paul: Films, predominantly. Kelly Molson: Wow. I mean, my husband would absolutely agree with you. So I got him to watch the first one and then we got halfway through the second one and he paused it and looked at me and said, "Kelly, I just can't do this. Sorry." And left the room. That was it. Done. Joseph Paul: I can understand. So in our household, we alternate between Harry Potter and Lord of the Rings. So we compromise. We have a Harry Potter, then a Lord of the Rings, then go through. Kelly Molson: Is your partner Harry Potter, then? Joseph Paul: My wife is very much a Harry Potter fan. Kelly Molson: Interesting. That is quite controversial. How do you feel about that, David? David Green: Very disappointing. Joe, actually. Joseph Paul: Sorry to let you down. David Green: We might have to end this now, Joe.Kelly Molson: This beautiful relationship that we're going to talk about. End over Harry Potter.  David Green: Harry Potter and cheese straws. Kelly Molson: David, same question to you. What is your unpopular opinion? David Green: Didn't think I had any unpopular opinions until I started really thinking about it, but I have to say, my original this is really good either, really was dancing, non professional dancing. I mean, I'm not a dancer, I've got a body of a dad. I am a dad and my wife and my daughter are very good dancers and I think it's just years of standing by a bar at a wedding with that person, go, "Come on, get on the dance floor, come on." And they drag you up and then busting moves is probably the wrong description, but it's just looking around the room on the floor with other people sort of bobbing around awkwardly looking, and all the blokes tipped you looking at each other going, "Oh, get me home." It's that awkwardness, I find really difficult and I'm going to be cheeky. And another one, because I just remembered that concerts is another one, so you spend a fortune going to a concert. David Green: I took my daughter once to Ariana Grande and I'd just been dragged to Arctic Monkeys and we drove hours and hours to this place and my wife had got Rose lead, I think, which was I needed binoculars to even see the stage. I was absolutely freezing, completely freezing. I didn't dress appropriately, I was dressed in a shirt and tied, typically, because that was Arctic Monkeys. Kelly Molson: You went through a shirt and tied Arctic Monkeys? God said, "Well".David Green: I remember walking down to the bottom of the stadium, I'm freezing, I have to go and get some clothes, and they let me out and I had to buy Arctic Monkeys merchandise and I came up the steps wearing an Arctic Monkeys hoodie. Number one fan to my wife and daughter, absolutely laughing hilariously.  David Green: And I had to listen to the music for 2 hours and then I got home about three in the morning and my wife had promised me dinner out, went to Wild Bean Cafe at 01:00 A.M. on the way home. Kelly Molson: What a treat.David Green: Dancing and concert. Laura just sneaking next to one in. Kelly Molson: Well, no, I love this. I mean, it's like an elongation of it, isn't it? They go hand in hand.  I would be that person at a wedding, they're trying to get you on the dancefloor. Which made me start laughing and then I lost it. Shirt and tie at an Arctic Monkeys gig. What were you thinking? David Green: I don't know. Kelly Molson: I think that's my favourite unpopular opinion yet. Amazing. Thank you both for sharing. Shall we talk about some serious stuff? David Green: Have you cried on a podcast before?Kelly Molson: Before I've had a cry, I've definitely had a cry on the podcast, but a cry of laughter, I'm not sure that's really got me today. Right, serious stuff. We're going to talk about data today, which is very serious stuff. We all know the importance of data. We've talked about data hundreds and hundreds of times in various different guyses. On this podcast, however, we're going to talk about reporting today, but with a twist. So reporting is often usually about things that have already happened. We're looking at past visitor numbers, we're looking at how many visitors came and how much they spent in the cafe on a particular day, what the weather was like on a past particular day. So we can predict whether it might be like that this year. Kelly Molson: But Blenheim are doing something completely different with reporting, which, when we had a chat about it prior to this episode, it blew my mind a little bit. And it's such a brilliant case study. You need to share this with the world. Firstly, though, I want you to just, both of us, tell us a little bit about your role and your background. So, Joe, can you start first? Tell us a little bit about your role and how you came into it. Joseph Paul: Yeah, of course. So I've been in the industry for six years now within the visitor attraction industry, working at Vennersys, and my role is a Key Account Manager. So I work closely with our clients throughout the lifetime of their contracts, so making sure they are getting the most out of the system and that sort of return on investment they've put into the software they've purchased. So I've worked closely with David and the Blenheim team for about six years now, and prior to that, I was also in account management as well, within a software business. Kelly Molson: Great. David, over to you. David Green: Variable history with Blenheim. I think next year will be the 30th year when I first walked through the doors. So when I was studying at college, it was my first sort of part time weekend Christmas job, and I was a bubble up for the 11th Duke and Duchess, and that was great. If I got I know stuff. Kelly Molson: I feel like there's a podcast episode on its own about that part of your career. David Green: I'm not sure I could speak too much about that, but I remember when I finished college, my mother said, "What are you going to get a proper job?" And the phone rang and I ended up working at Blenheim. Moved into the clock tower at Blenheim. That was my first flat. It was quite incredible, I have to say. But after leaving when I was 21, I just changed direction. So I became a developer, so I learned to programme and I worked for a little agency in Abingdon for two doctors who were both very bright guys. Yeah, I just put the hours in and learned to programme and really, that probably led to where I am today. I learned very quickly to problem solve and learned very quickly how to develop things. David Green: So when I finally joined Blenheim again, full time enabled me to sort of trial new things very quickly, fail fast. And that kind of led to our first real time reporting platform, which I developed myself. Kelly Molson: Amazing. David Green: This was really a combination of seeing that the business had lots of data and seeing that a lot of the data was inputted in manually. So being able to develop something that could contextualise data in a better way, but get people looking at the data in a much faster way, I think that's where it started from. Kelly Molson: And that is what we're going to talk about today. You've got a really interesting job title. So you're Head of Innovation at Blenheim Palace. Are there many other heads of innovation in the sector? Because there's lots of kind of I mean, ALVA, for instance, brilliant organisation, they do lots of kind of individual meetups. So heads of marketing meetups, CEO meetups, head of visitor service meetups. I haven't seen them do a Head of Innovation meetup yet, so I question how many of you are there? David Green: I don't think there's very many at all, but the title is becoming more and more known, I think, across multiple sectors. And it was really the sort of creation I was Head of Digital at Lent for eight or nine years, and it was really the creation of Dominic Hare, our CEO, who saw the need for research development. The role is really about hunting for problems, and as much as we're well known for our visitor business, we have a thriving land business and a thriving real estate business. And I get to work across those three tiers, which is really exciting, hunting for problems. I get to work with universities, so we have a really strong university partnership, both at Oxford Brookes and the Oxford University. David Green: And this really allows us to bring in the latest research academics into a real world environment to solve problems together. So that's really exciting. But then the sort of second thing I work on as Head of Innovation is live data, so I have a data background, so it meant that very quickly I could bring all of our data into one place to drive greater insight. And then the third tier is looking at sort of customer experience changes. So if anyone sees my post on LinkedIn, you'll see we've brought in a new returnable cup scheme of all of our cups are RFID enabled. So looking at eradicating single use cups right the way through to a transformation project around implementing digital wallets and pulses. David Green: So there's lots of different things right the way through to encouraging our visas to come by green transport, which is very much tied into our 2027 pledge to become carbon neutral. Kelly Molson: That's lovely. Yeah. That's really interesting that you sit across so many different facets and it's not just about data and reporting and digital, really. So what we're going to talk about today is a particular project that you've both been involved in, and I'm going to kind of split this into two, because there's two areas that I kind of want to focus on. I want to hear about what the project is and all of the things and benefits that it's brought to Blenheim, which David's going to talk about. Kelly Molson: And then, Joe, I want to then come over to you and talk about how you kind of made this happen from a supplier perspective and the things that you need to work through together with your client and maybe some of the things that you've had to change and implement to be able to support your client, to do the things that they want to do with your system. So, David, I'm going to start with you. Can you give us kind of an overview of what this project is like, the background to it and then what led to that project happening? David Green: Background is like many organisations in this sector, we have lots and lots of data. Often we report out of proprietary systems, we then contextualise our data very well and I wanted to bring all the information to one area so we could really apply context but also look at in that data. So this sort of built off our first real time reporting platform that were able to get data into the hands of the operations teams, other teams, really quickly. But it wasn't really supportable just by me here at Blenheim. So were looking at one, finding a platform that we could utilise to allow us to get data out to feedball in a much more secure way. I was handling all the visualisations and things and there's better tools for that. So that's one of the reasons. David Green: The second thing is looking at data, I wanted to try out using AI to identify patterns. So what's the correlation between certain data sources? There's one, a group of visitors wearing wet coats. Does that have an impact on the environmental conditions? What's the optimal number of people that retail space to maximise their understand all those sorts of things were unanswered questions. So I engaged one of our Oxford Brookes relationships that we already had and we applied for what's called a Knowledge Transfer Partnership. So a KTP, which is match funded, that's Innovate UK match funded, and I highly recommend them as a starting point. And what that does, it brings in an associate who works full time. David Green: This project was, I think, 32 months, but also you get access to different parts of the university and in our case, we had access to the technical faculty as well as the business faculty. So you've got real experts in the field working with an associate that's embedded here, Lennon, that can help us solve that problem. And we're fortunate enough to win the application and the grant money and then we cloud on. So we called it a Smart Visitor Management System. That's the headline and really the two key subsystems of that was the customer insight and prediction. So we wanted to look at how we could predict business numbers. We know all of the knock on impacts of that in terms of better planning, reducing food waste, all those sorts of things. But then we also want to look at the visitor flow. David Green: So that's almost saying, "Well, where are visitors right now and where are they going to go next?" But they're the two sort of component parts. Kelly Molson: Such a brilliant introduction to AI as well, because I think it is such a current topic right now. And I was at a recent ALVA meeting where there was a phenomenal speaker talking about the implications of AI and the opportunities that it could bring. And I think there was a 50 - 50 split of the audience of 50% of them were terrified about this new technology and what it might potentially mean. And then 50% were really inspired by it and see these huge opportunities from it. But I think this is such a brilliant case study to show how it can be used to your advantage in a very non-scary way. David Green: I think with AI can be scary, but actually it's all about governance at the end of the day. And actually what we're doing is using machine learning to identify the patterns in large data sets to help us be better informed. Kelly Molson: What have been the benefits of implementing this kind of level of data reporting? So what have you been able to do that you couldn't previously do? David Green: Well, predictions is one. So ultimately we all budget. The first thing to probably say is that when we do contextual reporting, normally we access our data from a proprietary system and then bring it into some sort of spreadsheet and then try and tie it into a budget. That's sort of the first thing. It's really getting all of your data sets in a early. So we had budget, we had weather, we had advanced bookings, we had ticketing from different sort of platforms. And the starting point, before we talk too much about end benefits, were developing a data strategy in this centralised concept of a DataHub. So all of our data is in one place, and we're using APIs and direct connections and data signature Vennersys to bring data into one place. David Green: We also looked at platforms, environments, so were looking at Azure, we're a Microsoft business. So actually we decided Azure was the right sort of plan for us and we came up with a very broad strategy that said anything else we procure in the future has to best in class or it talks to the DataHub and often if it's best in class as an API. So you can get that information into one place. So that's the first thing. The joy of using something like Microsoft and other platforms are available, I would say, is to access the power platform. And the Power platform sort of answered the problem around how do we visualise our data, how do we automate some of our data and what data is missing and how can we collect it? David Green: So using things like Power BI and PowerApps, I think was really crucial. Once we had all of our sort of data organised, we had the pandemic and of course, one of the sort of big issues around predicting, certainly when you've got lots of data sets, you're trying to look at patterns in data and your data is finely structured, then you get hit by something like this and where are the patterns? What's changed? The business model completely changed. We were a 10% advanced booking business. Suddenly were either zero or 80 or 100 and then sort of now about 65. So that was a bit of a challenge as well. In terms of then looking at the missing data. And we'll talk a little bit maybe about sort of the centre network and how do we measure things in remote places. David Green: But ultimately the core of this project was the DataHub, the ability to bring everything into one place, ability to push that data out. So answering your question in a long winded way is really about getting the data into hands of people, to allow them to plan better, to be prepared for the day, what is likely to happen today, what are the patterns in that day? And this is where we develop things like a concept of similar day. So a similar day might be one that has similar number of pre bookings, has similar weather. We look at weather in terms of temperature, wind and rain. It might have a similarity in terms of an event day or a weekend or similar budget. And that concept allows us to look forward, which is great. The predictions tend to look at other things. David Green: So we have one naive prediction that looks at previous performance in terms of pre booking to predict forward. And then another one, we have what we call an adaptive prediction, which allows us to look at advanced bookings and then see the change in advanced bookings over time against budget, to then alert us to the fact that we might experience more visitors than expected on that particular day. Kelly Molson: Gosh, that's really powerful, isn't it? Does that mean that your team have access to kind of a dashboard that they can look at any given time and be like, “Okay, we can model next week based on these predictions?”David Green: Data is pretty much everywhere, so we have one really nice thing and we have this. When I built search platform was TV screens across all of our staff areas. We have a ten OD voltwim across Blenheim. Everyone has access to that data. And that could be how traffic is flowing on the driveway. We use ADPR to look at how busy traffic is outside of our park walls. We look at car park capacity. We look at how happy our staff are using what we call a mood metric. So we put those smiley buttons in staff areas to determine how well they think the day is going. So we have access to all of this sort of information, but also then sort of more business reporting through Power BI. David Green: So we have a series of what I've called sort of visual representations of activity, but also sort of data that we can export into Excel. So we do a lot of finance reporting as well through Power BI. Again, all reporting from that single source of the truth, which is the DataHub. And if anyone's going down this route, I always describe it, I call it the product hierarchy. I always describe it as the giant coin sorting machine, which means that we're comparing apples with apples. So if you've got a particular product type, let's say annual park or House park and gardens, or park and gardens, you budget against that item, against adult, child, concession, family, young adult, whatever, you create a product hierarchy that matches that to your actual ticketing sales. David Green: And it doesn't matter then who sells your ticket, you're matching to that same product hierarchy. So think of it as a giant column sourcing machine that then every five minutes builds that single source of the truth in a database, then can be report out either through digital screens locations or Power BI. So, lots of tunes. Kelly Molson: It's incredible that level of access that you can give people now that must have improved how the team feel about their working day. It must have really helped with kind of like team culture and team morale. David Green: Absolutely. One, it's about engaging. Our teams are really important. People are the most important commodity we have at Blenheim. So having a series of management accounts, they never see their impact of engaging our businesses and giving our business a really good time, focusing on that Net Promoter Score, giving them access to that information. So, well done, look at the impact is really important. So, yeah, it's been fairly transformational here at Blenheim. Kelly Molson: Wow. What do you think has been the biggest impact? David Green: I think access to the data, better planning, there's more to do. We're embedding these tools, people that trust these tools. It's no mean feat. So getting good. What's nice to see when things aren't coming through quite right or car park speeds and we say it is, it might be data pipeline that's got awry. People very quickly come to us and say, "It's missing." So, seven days a week our team is sort of monitoring and seeing people use it. Moodmetric is great. Our cleaners now, they clean our facilities based on usage because they can see how many people have used the loo's by using our sensor data. So that's again, it all impacts that Net Promoter Score. And I will say on Net Promoter, love it or hate it, Net Promoter Score is all about looking backwards. David Green: Typically what we try to do is to create the equivalent to on the day. What can we do about it right now? How busy is traffic flowing on a drive? Do we need to open another kiosk? How busy will the cafe get? Will we run out sandwiches? So we've got alerting looking at that comparison to similar day and are we trading above or below that? So again, we can send an alert to say, “Make some more sandwiches or do something else. The loos need a clean.” All of these sorts of things are built into the visitor management system to allow us to really optimise not just the visitor experience, but our staff engagement and experience as well. Kelly Molson: So you've got this really proactive approach to it, which actually makes you reactive on the day because you can move quicker, because you can make easier decisions about things. That's phenomenal. I love that the team have taken real ownership of that as well. I think embedding something like this, it can be quite challenging, right. People don't like change and these things feel a bit scary, but it feels like your team have really engaged with them and taken ownership of the system. David Green: Absolutely. It's no mean feat. Two challenges embedding something new like this. Absolutely. That's change management. The second thing is data pipelines, ensuring all of your sensors and everything is online and working. And when you're dealing with such high volume of data sets coming in, you really need to be absolutely on it. Second to the sort of broader and maybe more granular reporting, one other thing we've devised is a series of KPIs, which pretty much any attraction. David Green: Most might already have a series of KPIs, but KPIs to look forward. So actually in this moment in time, are we trading ahead or behind versus this time last year? So if you start comparing apples with apples at this moment in time, what was RMR's booking? We share these KPIs across the whole site and that could be relation to bookings or even spend per head versus budget spend per head for the next 30 days. David Green: Visually, we put these on all of our digital screens very quickly can identify when we need to do something, be driving that by marketing activity or celebrating success. We've got a very clear picture and that means everyone's along for the ride. Everyone gets access to this information. Kelly Molson: That's absolutely phenomenal. Joe, I'm going to come over to you now because I can only imagine what you were thinking when David came to you and said, "Right, we've got this idea, this is what we want to do." And you're one of the platforms. Vennersys is one of the platforms that has been working with him. I think it's quite a long relationship. Is it? It's about 16 years.Joseph Paul: 16, 17 years now, I think. Long relationship.David Green: Yeah. I was five. How old were you? Joseph Paul: Wasn't conceived yet. Kelly Molson: Wowzers. That is a long relationship. Okay, so I kind of want to know from you, Joe, to make this happen, what have you had to do differently as a supplier? So how have you had to interact with your clients' needs and what steps did you have to go to kind of understand what the outcome was going to be? Joseph Paul: Yeah, so I think firstly that the system has an enormous amount of data in it and I think the first step for us was to understand exactly what Blenheim were looking to get out of the system and plug into the sort of the DataHub that David was talking about. So that kind of comprised of some initial conversations of what they were trying to achieve. And then following that it was all about workshopping and making sure were going to present the data in the format that David and the team at Blenheim Palace required. Joseph Paul: Yeah, I think fundamentally it was just working closely with the team there and getting those requirements in detail and making sure weren't missing anything and really understanding everything they were trying to achieve and pushing that in a simple and easy format for the team to then push into their views and into their KPIs that they required. Really the main focus for us was pushing that data out to David and the team into that DataHub in that format that was easily accessible and sort of manipulated for them. Kelly Molson: I guess there's so much it's understanding what are the key know, what are the variables here, what are the key points that we need to do this and how do we go about doing this for you? Joseph Paul: Absolutely. Because there's a number of options and a number of different ways that data can be pushed to clients. So it's understanding what the best is for that client and their resource because that's also important. Not every attraction has unlimited resource or the expertise in house to sort of obtain that data, but also, even if they can obtain that data, they might not have that sort of resource to then create their own dashboards and create their own reporting tools from a repository. So it's really understanding every kind of asset and every level to that sort of client and then working closely with them to achieve their goal. So it might be more resource from our side or working closely with the expertise that they might have in house. Kelly Molson: Or suggesting that they might need to get extra expertise. So this is something that we talk about in terms of API integration all the time, is that it absolutely can be done with any of the systems that you have. If they have an API, yes, you can integrate it into whatever other system that you want. But who takes ownership of that internally? And do they have the capability and do they have the resource and do they have the capacity to do that? And if that's a no, who can be trained to do those things? And how do we facilitate that as well? Joseph Paul: Yeah, absolutely. And in this case, as David highlighted, he's clearly got the expertise himself and others around him to produce all these fantastic sort of views and dashboards that are displayed all around Blenheim Palace. So in this sort of example with Blenheim Palace, it was all about getting the data to them and making sure it was in a format that they could work with easily. Kelly Molson: And you've worked together, Joe, you said about six years. You've been at Vennersys now, but the organisation has worked with Blenheim for over 16 years, which is testament to the relationship and the product that you have. Has this process that you've been through together, has this changed or strengthened the kind of relationship between supplier and client? Joseph Paul: Yes, I think from our point of view, we like to see it as a partnership. I think David would agree, and we want to be a part of their journey, but also Blenheim and want to be a part of our journey. So we're helping one another to achieve our individual goals as a partnership. So that relationship goes from strength to strength and we continue to have those conversations, whether that's myself or others within the business, to Blenheim and pass around things that we're coming up against in the industry, but also vice versa. So if David's got his ear to the ground and has a suggestion around how our platform could be improved, that's fed back to us. Joseph Paul: And we have that back and forth between client and supplier, but we like to see it as a partnership and work closely with them to achieve their goals and also our goals together.David Green: I don't want to make Joe cry, because I've already made you cry, Kelly, but seriously, over that course of 17 years, and I'm sure lots of people listening to this podcast will realise that it's always challenging working with other suppliers. You have your ups and you have your downs, but we've had way more ups than we've had downs and our business has changed massively. We went through a process of becoming a charity, so suddenly gifted all the admissions was really important and Joe and the team really helped us achieve that. David Green: Vanbrugh was not a very good forward planner in terms of he was a great architect, but actually, we have a single point of entry and to try and gift aid so many visitors, we have a million visitors a year coming to them to try and gift aid such a large number on a driveway is really difficult. So actually, working through that gift aid at the gate process, we're looking at that gift aid opportunity was one of the key projects, really, that we work with Vennersys on. Kelly Molson: But that's where the good things come out of client supplier relationships, is that you're both challenging each other on what the objectives are and what the outcomes potentially could be. So you work in partnership together and then everybody gets the better outcome. When we first spoke about this topic, what I thought was brilliant is that you have such a great case study, you have such a great showcase piece here, both of you, for how you've worked together and what you've been able to develop. I've absolutely said that you need to pitch this as a talk at the Museum and Heritage Show because I think it's an absolutely brilliant topic for it. It's so current and something that other organisations can go away and kind of model on. Kelly Molson: I don't know if you saw, we had Nik Wyness on from the Tank Museum last season who came on and basically just he gives away his kind of process as to how they've developed their YouTube following and how they've developed kind of a sales strategy from it. And it's brilliant. He's great at kind of coming on and going, "Yeah, this is what I did, and this is what we did, and this is the process and here you go. Go and do it." And I think you have an opportunity to do that together, which I think is lovely. David Green: Isn't it nice though, that we don't feel in competition and we can work together? We created what we call The Continually Improvement and Innovation Group which we have lots of members who have joined from all different places, from Chatsworth to Be Lee to Hatfield Outs and so on and all that is a slack channel. It's a six monthly meeting where we all come together and we discuss our challenges. You talked about are there many head of innovations? Well, may not be, but actually sharing our insights and sharing our lessons learned is incredibly important and that's not just Blenheim, lots of other attractions are doing lots of brilliant things as well and we can learn from them. So really exciting, I think, to do that. David Green: And again, very open, I will say, and I'm not going to plug a gift aid company, but there's something called Swift Aid that we're just looking at and wow, can we do retrospective gift aiding? Is it worth lots of money for lots of attractions that have gift aid on their admissions? Yes, it is well worth looking that up. Ultimately they have a database of 8 million centralised gift aid declarations that you can utilise there's commission but it's well worth looking at. If anyone wants information, please just LinkedIn with me and we'll discuss them. Kelly Molson: Oh, I love that. Again, this comes back to what we've always said about how collaborative and open to sharing information this sector is. What we'll do is in the show notes listeners, we will link to both David and Joe's LinkedIn profiles. If you want to connect with them, feel free and then actually David, Joe, if there's anything you want to share that we can add into those as well that would be useful for listeners. Then we'll pop them in there as. Kelly Molson: Actually, David, I've got one more question for you on that Slack channel, which I think is really interesting. It's great that you've set that up. I think those kind of platforms are really good at just facilitating conversation and it's really good to understand what people are doing from a supplier perspective. Do you have suppliers as part of that conversation as well, or is it purely attractions? David Green: I've kept it, I'd say non commercial, but we have invited speakers into the group to come and talk about it. But at the moment it's a closed environment. I think most people are more comfortable having sort of open conversations, but what it's really good at doing is it could be a question about compliance or sustainability or returnable cuts is a good one. It could be varying topics and we can just provide access to the right people here at Blenheim and vice versa, and other organisations if we've got questions. So, yeah, it works, it's growing, it's open, it's not ours, it's everyone's. So if anyone wants to join it, then we'll stick a link at LinkedIn maybe on the plot cups at the end of this. Kelly Molson: Oh, Fab, that's brilliant. Yeah, great. I think that's a really nice way of doing it with suppliers as well. It's difficult, I think Joe and I would probably say all of these conversations are really interesting for us because it helps us understand the challenges that the sector has and it helps us understand how we can make the things that we do so much better. So it's hard sometimes when there's closed environments like that, but the sector does so brilliantly at putting on conferences and organisations that we can all be part of as well. And again, platforms like this where we can come on and share the things that we're doing.Kelly Molson: That brings me back to the last question for you, Joe, is about has this process between the two of you and what you've been able to build together, has that helped Vennersys  as a supplier build out other services that you can then offer to kind of the wider sector? Joseph Paul: Yeah, so I think through this journey we've realised that data is really critical, but we also realised, as we kind of mentioned before, that not everyone has the resource to build their own visualisations of data and linking those to their sort of key performance indicators. So we work with Power BI as well on behalf of our clients, so we can also visualise that data that's within our systems. And that's really to help them get the most out of the data that is in our system, but also in that sort of more real time scenario, rather than having to extract a report, put it that into an Excel and get that information out. Joseph Paul: So that's one service that's kind of come out of that relationship, but also expanding on our sort of open API as well. So additional endpoints so that clients can also extract that data in real time and that continues to grow with other clients as well as we sort of go down that journey with some other clients. So, absolutely. It's helped us sort of open up another avenue which has benefited other clients in the past couple of years, but also moving forward as we sort of expand on it.Kelly Molson: Brilliant. And that's the sign of true partnership, isn't it? There's been some incredible wins for both of you involved and it's brought new opportunities to both of the organisations. Thank you both for coming on and sharing this today. So we always end the podcast with book recommendations from our guests. So I wondered if you've both been able to pick a book that you'd like to share with our listeners today. What have you got for us? Joe, we'll start with you. Joseph Paul: Mine's a little bit out there. David Green: We know it's not Harry Potter, Joe. Kelly Molson: Absolutely not. Joseph Paul: Well, that would be a curveball if I started to plug the Harry Potter series. Hey. So recently, I was in Albania in Tirana and I was on a guided tour. And they were talking about the Ottoman period. And I realised I know nothing about the Ottoman history and I was interested about it more. Joseph Paul: So my in laws purchased a book called Lord Of The Horizons, which is all about the history of the Ottoman empire. So that's my current read at the moment. And if you're into your history and into your sort of empires, it's definitely worth a read. So that's my recommendation. The Lord of Horizons. Kelly Molson: Nice. Joe, we just got a little insight into some of your hobbies there and your likes that we didn't know about. Good. Okay. Thank you. David, what about you? David Green: Mine is The Hidden Life of Trees by Peter Wallaban. It's an incredible book. Now, I read lots of strategy books, data books. My wife thinks I'm really sad. This book is not any of that. This is about how trees communicate and I was absolutely enthralled with it. So this talks about them like arousal networks, how trees communicate through their roots, the noises and the sounds that trees make when they're struggling, when they're thirsty. It led to a lot of laughter on holiday with my daughter drawing pictures of trees with ears, but trees can actually hear. And from that, I was able to come back and look at one of our land projects where we're building a small solar farm at the moment, actually looking at the sort of benefits to soil health while we're putting solar on sort of fed degraded farmland. David Green: So we're using something called soil ecoacoustics that will allow us to listen to the sound of soil. So listen to soil for ultimately to index how healthy that soil is. So this one book has led to me reading a number of different research papers, cooking up with the universities to then test and trial something completely brilliant around identifying health through acoustics. So book is absolutely brilliant. There's a follow on book, but if you look at Peter Wallabin, he's written a number of books. Absolutely fascinating. Kelly Molson: Okay, wow. One, what an incredible book. I had no idea that trees could hear or talk. That's blown my mind a little bit, especially as someone who's a bit of a tree hugger. I'm not going to lie, I made a statement. I was with a client yesterday and were talking about AI. And I said, sometimes the conversations around AI just make me want to go outside and hug the tree in my back garden, take my shoes and socks off and just put my feet on the grass because I just want to connect with nature again and just get out of a tech world. So there's that. So I'm definitely going to buy that book. But two, how your mind works as well, how that book has taken you on a journey of innovation again into something connected but completely different.David Green: Again, it's really data. So you're welcome. We'll happily show you that site and put some headphones on you and we'll make this public as well, so hopefully we can share the secret sound of soil and other things as well. But really fascinating. Kelly Molson: That to me sounds like a David Attenborough show. Maybe we'll make it another podcast episode at some point. I'd love that. Thank you both for coming on and sharing today. As ever, if you want to win a copy of Joe and David's books, go over to our Twitter account, retweet this episode announcement with the words, I want Joe and David's books and you'll be in with a chance of winning them. Wow. Thank you for sharing. It's been an absolutely insightful podcast. There's lots of things that we're going to put in the show notes for you all. And as Joe and David said, please do. If you've got questions around what they've talked about today, feel free to connect and we'll pop a link to that Slack group in the show notes too, so you can join in with these conversations. Thank you both. David Green: Thank you. Joseph Paul: Thanks, Kelly. Kelly Molson:  Thanks for listening to Skip The Queue. If you've enjoyed this podcast, please leave us a five star review. It really helps others find us. And remember to follow us on Twitter for your chance to win the books that have been mentioned. Skip the queue is brought to you by Rubber Cheese, a digital agency that builds remarkable systems and websites for attractions that helps them increase their visitor numbers. You can find show notes and transcriptions from this episode and more over on our website, rubbercheese.com/podcast. The 2023 Visitor Attraction Website Report is now LIVE! Dive into groundbreaking benchmarks for the industryGain a better understanding of how to achieve the highest conversion ratesExplore the "why" behind visitor attraction site performanceLearn the impact of website optimisation and visitor engagement on conversion ratesUncover key steps to enhance user experience for greater conversionsDownload the report now for invaluable insights and actionable recommendations!

Mars Lan is Co-Founder and CTO of Metaphor, the modern data catalog that is described as the "Social Platform for Data." Metaphor was created by the founders of ⁠DataHub⁠ which is known as the leading open source metadata platform. Metaphor has raised over $10M from investors including Amplify, a16z, and Point72 Ventures. In this episode, we dig into the story behind Metaphor's creation - and why the team didn't build a managed service on top of DataHub, why Metaphor isn't open source, why sales funnel is the biggest benefit of building a company using open source & much more!

Shirshanka Das grew up on the eastern side of India, near Calcutta. He did well in school, and got into IIT, choosing Computer Science as his major. Post undergrad, he got his PhD at UCLA, eventually working at PayPal and Yahoo on massive architectural systems. Outside of tech, he's married with 2 kids, he's an accomplished Indian vocalist, and has a passion for swimming, which he states is his therapy.After spending over a decade at LinkedIn, Shirshanka had led the teams supporting all things data. He created a unified approach to data discovery, governance, and observability - while he was at the company. He open sourced the product, called DataHub, and eventually created a managed version.This is the creation story of Acryl Data.SponsorsCipherstashTreblleCAST AI FireflyTursoMemberstackLinksWebsite: https://www.acryldata.io/Website: https://datahubproject.io/LinkedIn: https://www.linkedin.com/in/shirshankadas/Support this podcast at — https://redcircle.com/code-story/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Summary Data systems are inherently complex and often require integration of multiple technologies. Orchestrators are centralized utilities that control the execution and sequencing of interdependent operations. This offers a single location for managing visibility and error handling so that data platform engineers can manage complexity. In this episode Nick Schrock, creator of Dagster, shares his perspective on the state of data orchestration technology and its application to help inform its implementation in your environment. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) This episode is brought to you by Datafold – a testing automation platform for data engineers that finds data quality issues before the code and data are deployed to production. Datafold leverages data-diffing to compare production and development environments and column-level lineage to show you the exact impact of every code change on data, metrics, and BI tools, keeping your team productive and stakeholders happy. Datafold integrates with dbt, the modern data stack, and seamlessly plugs in your data CI for team-wide and automated testing. If you are migrating to a modern data stack, Datafold can also help you automate data and code validation to speed up the migration. Learn more about Datafold by visiting dataengineeringpodcast.com/datafold (https://www.dataengineeringpodcast.com/datafold) You shouldn't have to throw away the database to build with fast-changing data. You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! It's the only true SQL streaming database built from the ground up to meet the needs of modern data products. Whether it's real-time dashboarding and analytics, personalization and segmentation or automation and alerting, Materialize gives you the ability to work with fresh, correct, and scalable results — all in a familiar SQL interface. Go to dataengineeringpodcast.com/materialize (https://www.dataengineeringpodcast.com/materialize) today to get 2 weeks free! Your host is Tobias Macey and today I'm welcoming back Nick Schrock to talk about the state of the ecosystem for data orchestration Interview Introduction How did you get involved in the area of data management? Can you start by defining what data orchestration is and how it differs from other types of orchestration systems? (e.g. container orchestration, generalized workflow orchestration, etc.) What are the misconceptions about the applications of/need for/cost to implement data orchestration? How do those challenges of customer education change across roles/personas? Because of the multi-faceted nature of data in an organization, how does that influence the capabilities and interfaces that are needed in an orchestration engine? You have been working on Dagster for five years now. How have the requirements/adoption/application for orchestrators changed in that time? One of the challenges for any orchestration engine is to balance the need for robust and extensible core capabilities with a rich suite of integrations to the broader data ecosystem. What are the factors that you have seen make the most influence in driving adoption of a given engine? What are the most interesting, innovative, or unexpected ways that you have seen data orchestration implemented and/or used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on data orchestration? When is a data orchestrator the wrong choice? What do you have planned for the future of orchestration with Dagster? Contact Info @schrockn (https://twitter.com/schrockn) on Twitter LinkedIn (https://www.linkedin.com/in/schrockn) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Dagster (https://dagster.io/) GraphQL (https://graphql.org/) K8s == Kubernetes (https://kubernetes.io/) Airbyte (https://airbyte.com/) Podcast Episode (https://www.dataengineeringpodcast.com/airbyte-open-source-data-integration-episode-173/) Hightouch (https://hightouch.com/) Podcast Episode (https://www.dataengineeringpodcast.com/hightouch-customer-data-warehouse-episode-168/) Airflow (https://airflow.apache.org/) Prefect (https://www.prefect.io) Flyte (https://flyte.org/) Podcast Episode (https://www.dataengineeringpodcast.com/flyte-data-orchestration-machine-learning-episode-291/) dbt (https://www.getdbt.com/) Podcast Episode (https://www.dataengineeringpodcast.com/dbt-data-analytics-episode-81/) DAG == Directed Acyclic Graph (https://en.wikipedia.org/wiki/Directed_acyclic_graph) Temporal (https://temporal.io/) Software Defined Assets (https://docs.dagster.io/concepts/assets/software-defined-assets) DataForm (https://dataform.co/) Gradient Flow State Of Orchestration Report 2022 (https://gradientflow.com/2022-workflow-orchestration-survey/) MLOps Is 98% Data Engineering (https://mlops.community/mlops-is-mostly-data-engineering/) DataHub (https://datahubproject.io/) Podcast Episode (https://www.dataengineeringpodcast.com/datahub-metadata-management-episode-147/) OpenMetadata (https://open-metadata.org/) Podcast Episode (https://www.dataengineeringpodcast.com/openmetadata-universal-metadata-layer-episode-237/) Atlan (https://atlan.com/) Podcast Episode (https://www.dataengineeringpodcast.com/atlan-data-team-collaboration-episode-179/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

Dr. Michel van Genderen, physician, AI leader and founder of the Datahub at Erasmus Medical Center in the Netherlands, shares his passion for ethical AI in hospitals.  Could AI be a game-changer for the health care industry? Dr. van Genderen thinks so, and explains the two biggest global health care challenges are the shortage of personnel and an increasing health care demand. He believes trustworthy AI could alleviate these pressures and solve clinical challenges faster. For example, Erasmus Medical Center developed an AI model used in the intensive care unit that decreases the administrative workload for nurses.  Using AI in a responsible, ethical and sustainable manner is crucial to its adoption in clinical settings so that health care professionals trust AI when they use it at the bedside. To develop and deploy AI models in clinical settings, a group of multidisciplinary teams comes together, including data scientists, data engineers, physicians, nurses, patients and more, which is the remit of the Datahub at Erasmus Medical Center. Adhering to ethical guidelines is crucial when teams develop models, monitor their performance and adopt them in clinical or operational settings. Dr. van Genderen is optimistic that all industries will be able to benefit from AI, as long as decisions made with analytics and AI are ethical, trustworthy, explainable and fair.

Cloner la voix de Manuel Davy et d'Elisabeth Zehnder pour vous proposer l'épisode en anglais tout en préservant fidèlement l'empreinte vocale des intervenants d'origine est une réalité ! Cette expérience se devait d'être réalisée par la Cité de l'IA dont la mission est d'aider les entreprises à démystifier et s'approprier le sujet de l'IA, en le rendant accessible aux dirigeants et à leurs collaborateurs. - Cloning the voices of Manuel Davy and Elisabeth Zehnder to bring you the episode in English while faithfully preserving the voiceprint of the original speakers is a reality! This experiment had to be carried out by the Cité de l'AI, whose mission is to help companies demystify and take ownership of the subject of AI, by making it accessible to managers and their staff. /// Elisabeth Zehnder is in charge of the DataHub, Adeo's digital domain. In this episode, she sheds light on the implementation and benefits of machine learning. Machine learning is the link between business and artificial intelligence. “We start with an idea, a need in the head of a data scientist or a sector manager, which we dig into and structure, to find out if it can enable us to create added value.” “Then there's the value of change ", explains Elizabeth. In addition to the financial benefits of machine learning, it can also help to reduce drudgery in the workplace, by reducing the number of low-value-added tasks. This sub-category of AI is also changing the mindset of professions: "It's no longer only up to us to fetch the data, the different professions will expose it to us, give us access to it, thanks to the tools that will have been provided to them. " In a group like Leroy Merlin, there is a wide variety of different professions and expertise: "It's our duty to distribute this model, this know-how, across all our digital and business teams. " Enjoy today's episode ! Les Carnets de l'IA is a podcast proposed by the Cité de l'IA. Animation : Manuel Davy Production : César Defoort | Natif.  Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

The Shred is a weekly roundup of who's raised funds, who's been acquired and who's on the move in the world of recruitment. The Shred is brought to you today by Jobcase.

Comment accélérer le déploiement des bonnes idées dans un groupe de 150 000 collaborateurs ? Cette semaine, parlons de la rencontre entre les métiers et l'IA avec Elisabeth Zehnder, Domain leader DataHub chez Adeo et Chief Data officer Leroy Merlin France. Pour Elisabeth Zehnder, l'intelligence artificielle doit être au service de la création de valeur. « On part d'une idée, d'un besoin dans la tête d'un data scientist ou d'un chef de secteur, que l'on structure pour savoir si elle peut nous permettre de créer de la valeur ajoutée. On s'efforce de se poser les bonnes questions en partant de l'utilisateur final. Ensuite, on se pose la question de la réalisation technique et du déploiement à large échelle. » Qui dit valeur ajoutée dit bien souvent ROI. « Dès le début, il faut piloter ses indicateurs de performance. Tout cela reste théorique avant de déployer mais c'est important de rentrer dans cet exercice pour avoir un certain intervalle de confiance qui sera challengé par la vraie vie », assure la Domain Leader du Data Hub d'ADEO. Avant d'élargir la notion de performance : « Il y a la valeur sonnante et trébuchante, et puis il y a la valeur de changement. Les projets d'IA facilitent indirectement l'innovation dans d'autres business ». ADEO mène un travail de fond sur les données au service du métier. « Si on veut avancer, les équipes doivent s'approprier les data. On a posé le principe que chacun est en charge de mettre à disposition ses données métier pour que tous ceux qui en ont besoin puissent les utiliser. Par ailleurs, on veut éviter qu'en réunion les collaborateurs passent du temps à fact-checker les chiffres. Donc on a mis en place un outil qui permet de certifier par le dashboard et le reporting. Ça demande un certain niveau d'exigence mais ça met un tampon pour avoir des données qui font foi. » Bonne écoute ! Les Carnets de l'IA est un podcast proposé par la Cité de l'IA. Animation : Manuel Davy Réalisation : César Defoort | Natif.   Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Many operators in Western Europe have implemented price increases for their fixed and mobile services or plan to do so in the future, attempting to offset inflationary pressure. In this podcast, Julia Martusewicz-Kulinska (Principal Analyst) and Tom Rebbeck (Partner) discuss the various price increasing strategies and opportunities it creates for market challengers, especially in countries with unbalanced market shares of subscribers.   The associated article can be find here. The article is based on the Western Europe telecoms market: trends and forecasts 2022–2027 report. The forecast numbers are available in Analysys Mason's DataHub.

Summary The customer data platform is a category of services that was developed early in the evolution of the current era of cloud services for data processing. When it was difficult to wire together the event collection, data modeling, reporting, and activation it made sense to buy monolithic products that handled every stage of the customer data lifecycle. Now that the data warehouse has taken center stage a new approach of composable customer data platforms is emerging. In this episode Darren Haken is joined by Tejas Manohar to discuss how Autotrader UK is addressing their customer data needs by building on top of their existing data stack. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their extensive library of integrations enable you to automatically send data to hundreds of downstream tools. Sign up free at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) Your host is Tobias Macey and today I'm interviewing Darren Haken and Tejas Manohar about building a composable CDP and how you can start adopting it incrementally Interview Introduction How did you get involved in the area of data management? Can you describe what you mean by a "composable CDP"? What are some of the key ways that it differs from the ways that we think of a CDP today? What are the problems that you were focused on addressing at Autotrader that are solved by a CDP? One of the promises of the first generation CDP was an opinionated way to model your data so that non-technical teams could own this responsibility. What do you see as the risks/tradeoffs of moving CDP functionality into the same data stack as the rest of the organization? What about companies that don't have the capacity to run a full data infrastructure? Beyond the core technology of the data warehouse, what are the other evolutions/innovations that allow for a CDP experience to be built on top of the core data stack? added burden on core data teams to generate event-driven data models When iterating toward a CDP on top of the core investment of the infrastructure to feed and manage a data warehouse, what are the typical first steps? What are some of the components in the ecosystem that help to speed up the time to adoption? (e.g. pre-built dbt packages for common transformations, etc.) What are the most interesting, innovative, or unexpected ways that you have seen CDPs implemented? What are the most interesting, unexpected, or challenging lessons that you have learned while working on CDP related functionality? When is a CDP (composable or monolithic) the wrong choice? What do you have planned for the future of the CDP stack? Contact Info Darren LinkedIn (https://www.linkedin.com/in/darrenhaken/?originalSubdomain=uk) @DarrenHaken (https://twitter.com/darrenhaken) on Twitter Tejas LinkedIn (https://www.linkedin.com/in/tejasmanohar) @tejasmanohar (https://twitter.com/tejasmanohar) on Twitter Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Autotrader (https://www.autotrader.co.uk/) Hightouch (https://hightouch.com/) Customer Studio (https://hightouch.com/platform/customer-studio) CDP == Customer Data Platform (https://blog.hubspot.com/service/customer-data-platform-guide) Segment (https://segment.com/) Podcast Episode (https://www.dataengineeringpodcast.com/segment-customer-analytics-episode-72/) mParticle (https://www.mparticle.com/) Salesforce (https://www.salesforce.com/) Amplitude (https://amplitude.com/) Snowplow (https://snowplow.io/) Podcast Episode (https://www.dataengineeringpodcast.com/snowplow-with-alexander-dean-episode-48/) Reverse ETL (https://medium.com/memory-leak/reverse-etl-a-primer-4e6694dcc7fb) dbt (https://www.getdbt.com/) Podcast Episode (https://www.dataengineeringpodcast.com/dbt-data-analytics-episode-81/) Snowflake (https://www.snowflake.com/en/) Podcast Episode (https://www.dataengineeringpodcast.com/snowflakedb-cloud-data-warehouse-episode-110/) BigQuery (https://cloud.google.com/bigquery) Databricks (https://www.databricks.com/) ELT (https://en.wikipedia.org/wiki/Extract,_load,_transform) Fivetran (https://www.fivetran.com/) Podcast Episode (https://www.dataengineeringpodcast.com/fivetran-data-replication-episode-93/) DataHub (https://datahubproject.io/) Podcast Episode (https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/) Amundsen (https://www.amundsen.io/) Podcast Episode (https://www.dataengineeringpodcast.com/amundsen-data-discovery-episode-92/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

Rocky Mankini drops by the podcast to talk about: • His journey from Computer Lab Assistant to DevOps Engineer • Working at UCLA vs. UC San Diego • DataHub and Kubernetes clusters • Magic: The Gathering and pet tortoises Transcript: https://bit.ly/3zFRldb

This episode covers a lot of ground, from an insecure OAuth flow (Booking.com) to a crazy JSON injection and fail-open login system (DataHub) to hacking Bluetooth smart locks (Megafeis-palm). And even a new ImageMagick trick for a local file read. Links and vulnerability summaries for this episode are available at: https://dayzerosec.com/podcast/193.html [00:00:00] Introduction [00:00:26] Traveling with OAuth - Account Takeover on Booking.com [00:13:25] Megafeis-palm: Exploiting Vulnerabilities to Open Bluetooth SmartLocks [00:22:46] GitHub Security Lab audited DataHub: Here's what they found [00:33:43] ImageMagick: The hidden vulnerability behind your online images [00:38:49] CI/CD secrets extraction, tips and tricks [00:39:30] A New Vector For “Dirty” Arbitrary File Write to RCE The DAY[0] Podcast episodes are streamed live on Twitch twice a week: -- Mondays at 3:00pm Eastern (Boston) we focus on web and more bug bounty style vulnerabilities -- Tuesdays at 7:00pm Eastern (Boston) we focus on lower-level vulnerabilities and exploits. We are also available on the usual podcast platforms: -- Apple Podcasts: https://podcasts.apple.com/us/podcast/id1484046063 -- Spotify: https://open.spotify.com/show/4NKCxk8aPEuEFuHsEQ9Tdt -- Google Podcasts: https://www.google.com/podcasts?feed=aHR0cHM6Ly9hbmNob3IuZm0vcy9hMTIxYTI0L3BvZGNhc3QvcnNz -- Other audio platforms can be found at https://anchor.fm/dayzerosec You can also join our discord: https://discord.gg/daTxTK9

Summary The ecosystem for data professionals has matured to the point that there are a large and growing number of distinct roles. With the scope and importance of data steadily increasing it is important for organizations to ensure that everyone is aligned and operating in a positive environment. To help facilitate the nascent conversation about what constitutes an effective and productive data culture, the team at Data Council have dedicated an entire conference track to the subject. In this episode Pete Soderling and Maggie Hays join the show to explore this topic and their experience preparing for the upcoming conference. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? We feel your pain. It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze. It ends up being anything but that. Setting it up, integrating it, maintaining it—it's all kind of a nightmare. And let's not even get started on all the extra tools you have to buy to get it to do its thing. But don't worry, there is a better way. TimeXtender takes a holistic approach to data integration that focuses on agility rather than fragmentation. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. If you're fed up with the 'Modern Data Stack', give TimeXtender a try. Head over to dataengineeringpodcast.com/timextender (https://www.dataengineeringpodcast.com/timextender) where you can do two things: watch us build a data estate in 15 minutes and start for free today. Your host is Tobias Macey and today I'm interviewing Pete Soderling and Maggie Hays about the growing importance of establishing and investing in an organization's data culture and their experience forming an entire conference track around this topic Interview Introduction How did you get involved in the area of data management? Can you describe what your working definition of "Data Culture" is? In what ways is a data culture distinct from an organization's corporate culture? How are they interdependent? What are the elements that are most impactful in forming the data culture of an organization? What are some of the motivations that teams/companies might have in fighting against the creation and support of an explicit data culture? Are there any strategies that you have found helpful in counteracting those tendencies? In terms of the conference, what are the factors that you consider when deciding how to group the different presentations into tracks or themes? What are the experiences that you have had personally and in community interactions that led you to elevate data culture to be it's own track? What are the broad challenges that practitioners are facing as they develop their own understanding of what constitutes a healthy and productive data culture? What are some of the risks that you considered when forming this track and evaluating proposals? What are your criteria for determining whether this track is successful? What are the most interesting, innovative, or unexpected aspects of data culture that you have encountered through developing this track? What are the most interesting, unexpected, or challenging lessons that you have learned while working on selecting presentations for this year's event? What do you have planned for the future of this topic at Data Council events? Contact Info Pete @petesoder (https://twitter.com/petesoder) on Twitter LinkedIn (https://www.linkedin.com/in/petesoder) Maggie LinkedIn (https://www.linkedin.com/in/maggie-hays) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Data Council (datacouncil.ai/austin) Podcast Episode (https://www.dataengineeringpodcast.com/data-council-data-professional-community-episode-96) Data Community Fund (https://www.datacommunity.fund) DataHub (https://datahubproject.io/) Podcast Episode (https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/) Database Design For Mere Mortals (https://amzn.to/3ZFV6dU) by Michael J. Hernandez (affiliate link) SOAP (https://en.wikipedia.org/wiki/SOAP) REST (https://en.wikipedia.org/wiki/Representational_state_transfer) Econometrics (https://en.wikipedia.org/wiki/Econometrics) DBA == Database Administrator (https://www.careerexplorer.com/careers/database-administrator/) Conway's Law (https://en.wikipedia.org/wiki/Conway%27s_law) dbt (https://www.getdbt.com/) Podcast Episode (https://www.dataengineeringpodcast.com/dbt-data-analytics-episode-81/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

Data en analytics spelen een steeds belangrijkere rol voor het creëren van de IC van de toekomst. Tijdens SAS Innovate spreken hosts Jurjen en Walter met Michel van Genderen en Antonie Berkel. Michel is internist intensivist bij Erasmus MC en de co-founder van de Datahub. Antonie is technisch verantwoordelijk voor de accounts van SAS binnen de overheid en de gezondheidszorg.  In deze aflevering vertelt Michel van Genderen hoe hij zich inzet om de IC van de toekomst vorm te geven als plek waar zorgprofessionals met plezier werken en optimaal worden ondersteund door technologie. Vanuit zijn praktijkervaring legt Michel uit hoe het ziekenhuis data beschikbaar maakt vanuit verschillende systemen om hiermee mensgerichte innovaties te ontwikkelen die als doel hebben om de werkdruk van de zorgprofessional te verlagen en kwalitatief hoogwaardige zorg te kunnen leveren met de capaciteit die nodig is. Antonie gaat in op het belang van datagedreven zorg en de synergie tussen de medische en technische wereld.De Dataloog is de onafhankelijke Nederlandstalige podcast over data & kunstmatige intelligentie. Hier hoor je alles wat je moet weten over de zin en onzin van data, de nieuwste ontwikkelingen en echte verhalen uit de praktijk. Onze hosts houden het altijd begrijpelijk, maar schuwen de diepgang niet. Vind je De Dataloog leuk? Abonneer je op de podcast en laat een review achter.

Show Notes(01:41) Mars walked through his education studying Computer Systems Engineering at The University of Auckland in New Zealand.(03:16) Mars reflected on his overall Ph.D. experience in Computer Science at UCLA.(05:55) Mars discussed his early research paper on a robust and scalable lane departure warning system for smartphones.(07:13) Mars described his work on SmartFall, an automatic fall detection system to help prevent the elderly from falling.(08:34) Mars explained his project WANDA, an end-to-end remote health monitoring and analytics system designed for heart failure patients.(10:06) Mars recalled learnings from interning as a software engineer at Google during his Ph.D.(14:54) Mars discussed engineering challenges while working on PHP for Google App Engine and Gboard personalization during his subsequent four years at Google.(19:05) Mars rationalized his decision to join LinkedIn to lead an engineering team that builds the core metadata infrastructure for the entire organization.(21:15) Mars discussed the motivation behind the creation of LinkedIn's generalized metadata search and discovery tool, DataHub, later open-sourced in 2020.(25:21) Mars dissected the key architecture of DataHub, which is designed to address the key scalability challenges coming in four different forms: modeling, ingestion, serving, and indexing.(28:50) Mars expressed the challenges of finding DataHub's early adopters internally at LinkedIn and externally later on at other companies.(35:22) Mars shared the story behind the founding of Metaphor Data, which he co-founded with Pardhu Gunnam and Seyi Adebajo and currently serves as the CTO.(41:55) Mars unpacked how Metaphor's modern metadata platform serves as a system of record for any organization's data ecosystem.(48:07) Mars described new challenges with metadata management since the introduction of the modern data stack and key features of a great modern metadata platform (as brought up in his in-depth blog post with Ben Lorica).(53:55) Mars explained how a modern metadata platform fits within the broader data ecosystem.(58:30) Mars shared the hurdles to finding Metaphor Data's early design partners and lighthouse customers.(01:04:33) Mars shared valuable hiring lessons to attract the right people who are excited about Metaphor's mission.(01:07:28) Mars shared important culture-building lessons to build out a high-performing team at Metaphor.(01:10:45) Mars shared fundraising advice for founders currently seeking the right investors for their startups.(01:13:22) Closing segment.Mars' Contact InfoTwitterLinkedInGoogle ScholarGitHubMetaphor DataWebsite | Twitter | LinkedInCareers | About PageData Documentation | Data CollaborationMentioned ContentArticlesDataHub: A generalized metadata search and discovery tool (Aug 2019)Open-sourcing DataHub: LinkedIn's metadata search and discovery platform (Feb 2020)Founding Metaphor Data (Dec 2020)Metaphor and Soda partner to unify the modern data stack with trusted data (Dec 2021)Introducing Metaphor: The Modern Metadata Platform (Nov 2021)The Modern Metadata Platform: What, Why, and How? (Jan 2022)PapersSmartLDWS: A robust and scalable lane departure warning system for the smartphones (Oct 2009)SmartFall: An automatic fall detection system based on subsequence matching for the SmartCane (April 2009)WANDA: An end-to-end remote health monitoring and analytics system for heart failure patients (Oct 2012)PeopleBenn Stancil (Chief Analytics Officer at Mode Analytics, Well-Known Substack Writer)Tristan Handy (Co-Founder and CEO of dbt Labs, Writer of The Analytics Engineering Roundup)Andy Pavlo (Associate Professor of Database at Carnegie Mellon University)Books“Working In Public” (by Nadia Eghbal)“The Mom Test” (by Rob Fitzpatrick)“A Thousand Brains” (by Jeff Hawkins)“The Scout Mindset” (by Julia Galef)NotesMy conversation with Mars was recorded back in January 2022. Since then, many things have happened at Metaphor Data. I'd recommend:Visiting their brand new websiteReading the 3-part “Data Documentation” series on their blog (part 1, part 2, and part 3)Looking over the Trusted Data landing pageAbout the showDatacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you're new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Datahub : définition(s) et approche. Data stratégie : comment mieux intégrer et gérer la données dans l'entreprise

In de 20ste aflevering van onze podcast, praten we Ruiter Janssen. We kennen Ruiter als één van de organisatoren van het jaarlijkse Infographics Congres in Hilversum. Hij is van beroep ‘design researcher' en is in dienst bij de Algemene Rekenkamer en hij is eigenaar van de Studio Janssen. We praten met Ruiter over zijn opleidingen, zijn carrière en natuurlijk over het Infographics Congres. Dit congres zal dit jaar zijn op 2 september. Natuurlijk hebben we veel meer besproken en heeft hij hele goede tips voor de luisteraars. Wil je meer weten en het gehele gesprek met Ruiter beluisteren? Klik dan om deze 20ste aflevering te beluisteren. Hier nog enkele interessante links: · Volg hem op LinkedIn: https://www.linkedin.com/in/ruiterjanssen/ · Volg de website van zijn studio met een overzicht van zijn werk: https://www.ruiterjanssen.nl/ · Volg hem op Instagram: https://www.instagram.com/ruiterjanssen/ · Volg ook de website van het Infographic Congres: https://www.infographicscongres.eu/ Heb je vragen, tips of andere opbouwende feedback voor ons, laat dit ons dan weten via: michel@datavoorstellingen.nl of ben@datavoorstellingen.nl. #dataliteracy #datadriven #dataviz #datavisualisation #datavisualiseren #datadesign #storytelling #design #dataart #visualisingdata #futureofaudits #DesignAuditStudio #design #DataHub #publicsectorinnovation

As the Russian invasion enters its twelfth day, fuel prices hit new records in the UK. Global leaders are preparing for the worst, is the UK braced for this too? Also on the podcast, what's behind Boris Johnson's six-point plan? 'I would far rather Boris Johnson wasn't turning away Ukrainian refugees at the border in Calais than coming up with the six-point plan' - Fraser Nelson. All to be discussed as Kay Balls speaks to Fraser Nelson and James Forsyth.  For more information on the Russian nation, The Spectator is covering the economic impacts of the Ukraine-Russia war on our Datahub.

Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB) In this episode, Scott interviews Sheetal Pratik, Director of Engineering, Data Integration at Adidas. If Sheetal's name sounds familiar to data mesh officianados, she presented at the Data Mesh Learning meetup in August 2021. Sheetal is passionate about giving companies the permission AND a workable plan for getting started with data mesh. She covered a wide range of things regarding getting starting but a few really stood out: Don't try to tackle tomorrow's challenges today Break your implementation into phases: development, adoption, and scaling Start your initial data mesh MVP with a simple data product with a simple schema - your goal is to develop the "muscles" around creating and deploying data products rather than shooting for a high-value product first Keep to a reasonable budget and prove viability and value Sheetal also covered how much you really have to have in place to create and evaluate your MVP. There will always be evolution and change and your organization has to be ready for that. That can be frightening or inspirational. Sheetal chooses it as inspirational - it gives you the freedom to move quickly as long as the organization understands that things will change in the future. She wrapped up with saying that data mesh shouldn't be scary, you should be excited about this journey and what it can mean for your organization. Get an MVP out the door, it will take time, don't get ahead of yourself. Data mesh success can happen if you let it. Sheetal's (and Divya and Madhu from Thoughtworks) Data Mesh Learning Meetup presentation: https://www.youtube.com/watch?v=5btUaLPdaNk (https://www.youtube.com/watch?v=5btUaLPdaNk) Sheetal's post re data mesh and using DataHub: https://blog.datahubproject.io/enabling-data-discovery-in-a-data-mesh-the-saxo-journey-451b06969c8f (https://blog.datahubproject.io/enabling-data-discovery-in-a-data-mesh-the-saxo-journey-451b06969c8f) Sheetal's LinkedIn: https://www.linkedin.com/in/sheetalpratik/ (https://www.linkedin.com/in/sheetalpratik/) Data Governance using Data Mesh paper: https://easychair.org/publications/preprint/qZ3m (https://easychair.org/publications/preprint/qZ3m) Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him at community at datameshlearning.com or on LinkedIn: https://www.linkedin.com/in/scotthirleman/ (https://www.linkedin.com/in/scotthirleman/) If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/ (https://datameshlearning.com/community/) If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see https://docs.google.com/document/d/1WkXLhSH7mnbjfTChD0uuYeIF5Tj0UBLUP4Jvl20Ym10/edit?usp=sharing (here) All music used this episode created by Lesfm (intro includes slight edits by Scott Hirleman): https://pixabay.com/users/lesfm-22579021/ (https://pixabay.com/users/lesfm-22579021/) Data Mesh Radio is brought to you as a community resource by DataStax. Check out their high-scale, multi-region database offering (w/ lots of great APIs) and use code DAAP500 for a free $500 credit (apply under "add payment"): https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB)

Pardhu Gunnam (CEO @ Metaphor) and Mars Lan (CTO @ Metaphor) - also both co-creators of LinkedIn's DataHub - join the Monday Morning Data Chat to talk about metadata + data catalogs. #datacatalog #metadata #dataengineering --------------------------------- TERNARY DATA We are Matt and Joe, and we're "recovering data scientists". Together, we run a data architecture company called Ternary Data. Ternary Data is not your typical data consultancy. Get no-nonsense, no BS data engineering strategy, coaching, and advice. Trusted by great companies, both huge and small. Ternary Data Site - https://ternarydata.com LinkedIn - https://www.linkedin.com/company/ternary-data/ YouTube - https://www.youtube.com/channel/UC3H60XHMp6BrUzR5eUZDyZg

Pardhu Gunnam (CEO) and Mars Lan (CTO), are co-founders of Metaphor Data, creators of the first Modern Metadata Platform. As we noted in a previous post, a metadata fabric is the right foundation for data governance and data discovery solutions, data catalogs, and other enterprise data services. This insight resulted in several metadata systems being created within technology companies a few years ago. In fact, the team at Metaphor created one of the more popular systems – DataHub – while they were at Linkedin.Video version has a detailed table of contents:  https://www.youtube.com/watch?v=W8ZJHN77IegSubscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

What does metadata really mean? Data scientist Shirshanka Das joins The Data Wranglers, Joe Hellerstein, Jeffrey Heer and Adam Wilson, to re-define metadata. Das discusses his innovative work in data, including a decade at LinkedIn where he was part of a now-legendary data cabal that coined the term "data science" and built the open-source engineering tools Kafka, Pinot and DataHub. Recently, Shirshanka co-founded a new company, Acryl Data, to support the DataHub open-source project. #TheDataWranglers

The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn's data needs. It was also designed to be able to work for small scale systems that are just starting to develop in complexity. In order to support the project and make it even easier to use for organizations of every size Shirshanka Das and Swaroop Jagadish founded Acryl Data. In this episode they discuss the recent work that has been done by the community, how their work is building on top of that foundation, and how you can get started with DataHub for your own work to manage data discovery today. They also share their ambitions for the near future of adding data observability and data quality management features.

Swaroop Jagadish, Co-Founder & CTO of Acryl Data, joins Hashmap on Tap host, Kelly Kohlleffel to discuss how Acryl Data is bringing more clarity to your data using a next-generation multi-cloud metadata management platform and developer-friendly data catalog powered by LinkedIn DataHub. Swaroop also talks about the fascinating journey that led him to this latest venture. Show Notes: Check out Acryl Data: https://www.acryldata.io/ Join the DataHub Community: https://datahubproject.io/ Connect with Swaroop on LinkedIn: https://www.linkedin.com/in/swaroopjagadish/ Data discovery in Data Mesh by Saxo Bank: https://medium.com/datahub-project/enabling-data-discovery-in-a-data-mesh-the-saxo-journey-451b06969c8f On tap for today's episode: a Cappucino & Nespresso espresso Altissio Contact Us: https://www.hashmapinc.com/reach-out

In this episode of Ventures, I sit down with Yannick Folla (https://twitter.com/y_folla) to discuss an introduction to Web 3 for product managers looking to get quickly up to speed to add value to the Web 3 ecosystem. We discuss practical aspects of how to build with DeFi, NFTs, DAOs, decentralized patterns, specific networks, layer 1 vs. layer 2 technologies, and more. We also take specific product development examples within Figment.io's business and use those as teaching opportunities for a broad audience. Visit https://satchel.works/@wclittle/ventures-episode-65 for detailed notes and links to resources (videos, articles, etc…) mentioned. You can watch this episode via video here.2:20 - Yannick's background and story into the Web 3 world, joining Figment, and building products.11:08 - Starting with Figment's staking service, with the products of the staking dashboard and Hubble (https://hubble.figment.io/ ), how did Yannick and team approach building the products for the audiences they serve?13:24 - Product evolution/iteration nuances of Hubble14:40 - DataHub (https://figment.io/datahub/) - similar to Heroku for Web 3 - how to educate a Web 3 PM in the context of how Yannick and team have built DataHub18:39 - User experience needs/opportunities that drove the development of DataHub20:22 - Figment Learn (https://learn.figment.io/) - how is this available to help train Web 3 PMs and the developers that would be on teams to build dApps?22:50 - What are folks going to first learn when going through Figment Learn (APIs, Balances, querying, creating a wallet, and posting a transaction) 25:04 - Running through an example of doing a decentralized version of Twitter, how would a Web 3 PM need to restructure their thinking to build such an application? 28:30 - Homework for primitives for Web 3. DeFi, NFTs, DAOs, https://a16z.com/2018/02/10/crypto-readings-resources/ // https://www.matthewball.vc/the-metaverse-primer // Web 3 is coming up to it's “iPhone moment” and Yannick believes it's going to be intricately related to the metaverse31:03 - Aspects/definitions of Web 3 (metaverse, semantic web, blockchains/decentralization). Might be a 4th, a new generation of Internet where the value creators are the owners and capture the value. 32:09 - For a history lesson, why did the original wave of people attempting to decentralize existing Web 2 platforms fail? 34:03 - Decentralized governance - What do Web 3 PM need to know about decentralization/DAOs from a philosophical and practical approach? Multiple different types of DAOs and use cases. Thinking of subreddits as DAOs. 36:34 - What are the DAOs built on? How can someone start a DAO?37:59 - is this the same Aragon from 3-4 years ago?40:28 - Let's talk about DeFi and NFTs. What are the best tools? Where can people learn more? Look at Uniswap (https://uniswap.org/), Aave (https://aave.com/), and YFI 44:17 - How hard is it to spin up an NFT club?46:00 - NFT types (ERC 721 & 1151) 46:39 - Anything else for Yannick to add to the conversation? Keep learning. Be active on Twitter (big source of knowledge). 47:43 - Where can people find Yannick online to continue the conversation? https://twitter.com/y_folla 

Brown University Economist Emily Oster returned to the news last week when her team launched their new "COVID-19 School Datahub." The Datahub seems to suggest that the most pressing consequence of the pandemic has been...shifts to remote learning. We explain why Oster's data--and the claims she derives from it--is so troubling (and so lucrative). Transcript: https://docs.google.com/document/d/1taL0yOkdAv1GaLCVWW4lZ-Qb3BVewHYgU8FCrt0dPck/edit?usp=sharing --- Send in a voice message: https://anchor.fm/residential-spread/message

Show Notes(01:48) Sarah talked about the formative experiences of her upbringing: growing up interested in the natural sciences and switching focus on terrorism analysis after experiencing the 9/11 tragedy with her own eyes.(04:07) Sarah discussed her experience studying International Security Studies at Stanford and working at the Center for International Security and Cooperation.(07:15) Sarah recalled her first job out of college as a Program Director at the Center for Advanced Defense Studies — collaborating with academic researchers to develop computational approaches that counter terrorism and piracy.(09:48) Sarah went over her time as a cyber-intelligence analyst at Cyveillance, which provided threat intelligence services to enterprises worldwide.(12:22) Sarah walked over her time at Palantir as an embedded analyst, where she observed the struggles that many agencies had with data integration and modeling challenges.(15:26) Sarah unpacked the challenges of building out the data team and applying the data work at Mattermark.(20:15) Sarah shared her opinion on the career trajectory for data analysts and data scientists, given her experience as a manager for these roles.(23:43) Sarah shared the power of having a peer group and building a team culture that she was proud of at Mattermark.(26:41) Sarah joined Canvas Ventures as a Data Partner in 2016 and shared her motivation for getting into venture capital.(29:47) Sarah revealed the secret sauce to succeed in venture — stamina.(32:00) Sarah has been an investor at Amplify Partners since 2017 and shared what attracted her about the firm's investment thesis and the team.(35:28) Sarah walked through the framework she used to prove her value upfront as the new investor at Amplify.(38:35) Sarah shared the details behind her investment on the Series A round for OctoML, a Seattle-based startup that leverages Apache TVM to enable their clients to simply, securely, and efficiently deploy any model on any hardware backend.(44:39) Sarah dissected her investment on the seed round for Einblick, a Boston-based startup that builds a visual computing platform for BI and analytics use cases.(48:45) Sarah mentioned the key factors inspiring her investment in the seed round for Metaphor Data, a meta-data platform that grew out of the DataHub open-source project developed at LinkedIn.(53:57) Sarah discussed what triggered her investment in the Series A round for Runway, a New York-based team building the next-generation creative toolkit powered by machine learning.(58:36) Sarah unpacked the advice she has been giving her portfolio companies in hiring decisions and expanding their founding team (and advice they should ignore).(01:01:29) Sarah went over the process of curating her weekly newsletter called Projects To Know (active since 2019).(01:05:00) Sarah predicted the 3 trends in the data ecosystem that will have a disproportionately huge impact in the future.(01:11:15) Closing segment.Sarah's Contact InfoAmplify PageTwitterLinkedInMediumAmplify Partners' ResourcesWebsiteTeamPortfolioBlogMentioned ContentBlog PostsOur Investment in OctoMLAnnouncing Our Investment in EinblickOur Investment in Metaphor DataOur Series A Investment in RunwayPeopleSunil Dhaliwal (General Partner at Amplify Partners)Mike Dauber (General Partner at Amplify Partners)Lenny Pruss (General Partner at Amplify Partners)Mike Volpi (Co-Founder and Partner at Index Ventures)Gary Little (Co-Founder and General Partner at Canvas Ventures)Book“Zen and the Art of Motorcycle Maintenance” (by Robert Pirsig)New UpdatesSince the podcast was recorded, Sarah has been keeping her stamina high!Her investments in Hex (data workspace for teams) and Meroxa (real-time data platform) have been made public.She has also spoken at various panels, including SIGMOD, REWORK, University of Chicago, and Utah Nerd Nights.Be sure to follow @sarahcat21 on Twitter to subscribe to her brain on the intersection of data, VC, and startups!

Show Notes(01:48) Sarah talked about the formative experiences of her upbringing: growing up interested in the natural sciences and switching focus on terrorism analysis after experiencing the 9/11 tragedy with her own eyes.(04:07) Sarah discussed her experience studying International Security Studies at Stanford and working at the Center for International Security and Cooperation.(07:15) Sarah recalled her first job out of college as a Program Director at the Center for Advanced Defense Studies — collaborating with academic researchers to develop computational approaches that counter terrorism and piracy.(09:48) Sarah went over her time as a cyber-intelligence analyst at Cyveillance, which provided threat intelligence services to enterprises worldwide.(12:22) Sarah walked over her time at Palantir as an embedded analyst, where she observed the struggles that many agencies had with data integration and modeling challenges.(15:26) Sarah unpacked the challenges of building out the data team and applying the data work at Mattermark.(20:15) Sarah shared her opinion on the career trajectory for data analysts and data scientists, given her experience as a manager for these roles.(23:43) Sarah shared the power of having a peer group and building a team culture that she was proud of at Mattermark.(26:41) Sarah joined Canvas Ventures as a Data Partner in 2016 and shared her motivation for getting into venture capital.(29:47) Sarah revealed the secret sauce to succeed in venture — stamina.(32:00) Sarah has been an investor at Amplify Partners since 2017 and shared what attracted her about the firm's investment thesis and the team.(35:28) Sarah walked through the framework she used to prove her value upfront as the new investor at Amplify.(38:35) Sarah shared the details behind her investment on the Series A round for OctoML, a Seattle-based startup that leverages Apache TVM to enable their clients to simply, securely, and efficiently deploy any model on any hardware backend.(44:39) Sarah dissected her investment on the seed round for Einblick, a Boston-based startup that builds a visual computing platform for BI and analytics use cases.(48:45) Sarah mentioned the key factors inspiring her investment in the seed round for Metaphor Data, a meta-data platform that grew out of the DataHub open-source project developed at LinkedIn.(53:57) Sarah discussed what triggered her investment in the Series A round for Runway, a New York-based team building the next-generation creative toolkit powered by machine learning.(58:36) Sarah unpacked the advice she has been giving her portfolio companies in hiring decisions and expanding their founding team (and advice they should ignore).(01:01:29) Sarah went over the process of curating her weekly newsletter called Projects To Know (active since 2019).(01:05:00) Sarah predicted the 3 trends in the data ecosystem that will have a disproportionately huge impact in the future.(01:11:15) Closing segment.Sarah's Contact InfoAmplify PageTwitterLinkedInMediumAmplify Partners' ResourcesWebsiteTeamPortfolioBlogMentioned ContentBlog PostsOur Investment in OctoMLAnnouncing Our Investment in EinblickOur Investment in Metaphor DataOur Series A Investment in RunwayPeopleSunil Dhaliwal (General Partner at Amplify Partners)Mike Dauber (General Partner at Amplify Partners)Lenny Pruss (General Partner at Amplify Partners)Mike Volpi (Co-Founder and Partner at Index Ventures)Gary Little (Co-Founder and General Partner at Canvas Ventures)Book“Zen and the Art of Motorcycle Maintenance” (by Robert Pirsig)New UpdatesSince the podcast was recorded, Sarah has been keeping her stamina high!Her investments in Hex (data workspace for teams) and Meroxa (real-time data platform) have been made public.She has also spoken at various panels, including SIGMOD, REWORK, University of Chicago, and Utah Nerd Nights.Be sure to follow @sarahcat21 on Twitter to subscribe to her brain on the intersection of data, VC, and startups!

In this episode of the DeFi Download, Piers Ridyard interviews Lorien Gabel, CEO of Figment.io. Figment offers complete solutions that make it simple for token holders and developers to use and build on blockchains at the infrastructure, middleware, and application layers.Lorien is a serial entrepreneur with more than 20 years of operational, technological, and marketing management focused on Internet infrastructure. Before Figment, he founded and scaled three successful start-ups (Interlog Internet Services, BOAW Networks and Pingg.com). He has also served on the senior leadership teams of two other high-growth technology ventures (MessageLabs and Web.com) and has mentored, advised, and directly invested in several start-ups.Figment is one of the world's largest blockchain staking and infrastructure providers. The Figment team envisions a truly decentralized Internet where users can freely interact, share, collaborate, and exchange goods and services in a trustless environment. Based in Canada, serving customers worldwide, Figment's mission is to build a better Internet using blockchain technology.[01:47] As the founder of an ISP, Lorien sees parallels between the early days of the internet and what is happening now in the blockchain.[09:19] Lorien describes himself as the chief stoic at Figment. Why did he make stoicism his life philosophy?[12:46] What did the Figment team notice in 2018 that prompted them to develop Figment?[17:27] For those who have never used a staking service, how does it work in theory? How does the Figment address things such as the security of people's tokens?[20:39] Explaining slashing for those who are unfamiliar with the term.[23:39] What the Figment team thinks they did well, and what they have learned in the three and a half years they have been staking and running their infrastructure.[27:00] Did Figment have a specific go-to-market strategy for a network segment? Or have they tried everything and discovered that a certain customer type is better for them?[29:57] APIs for developers are another aspect of Figment's business. Learn, DataHub, and Hubble are all products from Figment.[36:07] Everyone is aware that Ethereum is transitioning to proof-of-stake, but few are aware of where it is currently and when it will be completed. What is Figment doing to prepare for the proof-of-stake transition?[39:47] What are Lorien's thoughts on Maximum Extractable Value (MEV) strategies, and does Figment intend to pursue them?Further resourcesWebsite: figment.io Twitter: @Figment_io Twitter: @lorientree Telegram: t.me/figmentnetworks 

I denne Dataklubben Special møder vi Martin Lervad Lundø, VP & CEO hos Energinet Datahub, og Christian Adelhart, Forretningsudvikler og passioneret data-entusiast. Faktisk var det Christian, der rakte ud til Dataklubben for at give alle jer lyttere og data-entusiaster en mulighed for at kigge nærmere på 8 års data i højeste kvalitet gennem den store DataHub på energidataportal.dk.   Med ambitionen om ”Grøn energi for en bedre verden” deler Energinet, DataHub gavmildt ud af idéer og viden om, hvordan data og digitalisering vil kunne løse en del problemstillinger rundt om i samfundet. DataHubben er en central og uafhængig it-platform, som faciliterer kommunikation blandt alle de professionelle aktørerne i elmarkedet. Er man aktør i det danske elmarked, kommunikerer man med Datahubben. Udover de kommercielle spillere er målet at aktivere en bred skare af iværksættere og data-nysgerrige for at accelerere den grønne omstilling. Og her kommer du, kære lytter, ind i billedet – har du kigget ind i dit eget el-datasæt?   Så længe vi ikke er herre over, hvornår vinden blæser eller solen skinner, bestemmer vi nemlig heller ikke, hvornår der er grøn energi. Så hvordan undgår man at tænde for de helt store kedler ved spidsbelastninger? Fleksibilitet og samtidighed nøgleord i den grønne omstilling, og den gode nyhed er, at ”Verden derude” bliver mere og mere fleksibel i forhold til forbrug. Mange startups er allerede godt i gang med at udnytte dette, fx Ento Labs, som arbejder med at spare energi og optimere bygninger, Vitani, der hjælper med at styre store virksomheders elforbrug, så det passer med fluktuerende energi og prisindex, eller True Energy, som hjælper elbilsejere med at vælge grøn strøm. Hvad gør du? Og hvad gør din virksomhed?    Uanset om du lytter med som privatperson eller som fagligt datanysgerrig, så kan du slutte dagens podcast med at starte på et nyt datasæt! Er du game? 

In this episode of Ventures, my guest Andrew Cronk (https://www.linkedin.com/in/andrewcronk/, Co-founder and Chief Product Officer at https://figment.io/) and I discuss Web 3 and blockchains beyond price hysteria, energy-usage debates, and influencer shenanigans. While everyone has been distracted by current events, the Web 3 builders continue to push the technology forward in a way that is genuinely compelling for our future. We talk about Proof-of-Stake, building a Web 3 developer community, technologies that exist today for decentralized apps, NFTs, Helium Network, what the rest of this year looks like for Figment, and much, much more. Visit https://satchel.works/@wclittle/ventures-episode-48 for detailed notes and links to resources (videos, articles, etc…) mentioned. You can watch this episode via video here.In this episode we cover the following:1:55 - Will's tee-up for the conversation and why he enjoys having Andy on the show, why coin price and market dynamics aren't as interesting as what blockchains are going to enable for humanity.2:33 - Andy intro, background of https://figment.io, their bet on Proof-of-Stake, and the products/services they've developed for the community (Hubble, DataHub, Figment Learn, etc…)5:44 - Why proof-of-stake? Why did Figment double-down there? (seems like 99% of new blockchains are launching with proof-of-stake, so not a bad bet)8:51 - Defining Web 3. Semantic Web. Looping in AI/XR. How does Andy think about and define Web 3?10:40 - What can we - the collective developer community - do right now? What tech is available? Is it possible to build a fully functional Web 3 decentralized app? 15:42 - What can a group of 300-400 people use on Web 3 right now to organize and communicate? 19:58 - Logging in with identity in a Web 3 way, high interest in building Web 3 dApps, https://ceramic.network/ 20:50 - Possible to store chat data on-chain? Or in a Layer 2-3? 23:30 - Are there chains right now to put data on publicly? FileCoin/IPFS, Arweave, Sia.Tech's SkyNet.24:25 - dApp developers are going to need to query a database (e.g. a relational database, SQL  databases), what's available around this in Web 3? 26:06 - The nuance: where your application logic runs. Much more like a serverless paradigm. 27:10 - Figment's new fund: https://figment.io/resources/figment-capital-16m-fund-to-grow-web-3/ 29:28 - Supporting companies in different ways as part of the investment thesis (similar to https://www.protaventures.com) 30:25 - Similar to Bezos asking about what can be done with the Internet to scale selling books, what are ways that blockchains are enabling new tech? 33:00 - A lot more happening around mutualization (insurance). Nexus Mutual. Unslashed Finance. 34:20 - A discussion about the Helium Network. The future of 5G penetration into cities/towns with Helium, the raw source of their bandwidth, StarLink, etc... 37:50 - What's next for Figment? They are hiring! → https://figment.io/jobs/ 40:37 - Anything else that listeners should know about or questions that Andy has in this space?

As the volume and scope of data collected by an organization grow, tasks such as data discovery and data management grow in complexity. Simply put, the more data there is, the harder it is for users such as data analysts to find what they're looking for. A metadata hub helps manage Big Data by providing metadata search and discovery tools, and a centralized hub which presents a holistic view of the data ecosystem. DataHub is Linkedin's open-sourced metadata search and discovery tool. It is Linkedin's second generation of metadata hubs after WhereHows. Pardhu Gunnam and Mars Lan join us today from Metaphor, a company they co-founded to build out the DataHub ecosystem. Pardhu and Mars, and the other co-founders of Metaphor, were part of the team at Linkedin that built the DataHub project. They join the show today to talk about how DataHub democratizes data access for an organization, why the new DataHub architecture was critical to Linkedin's growth, and what we can expect to see from the DataHub project moving forwards.

As the volume and scope of data collected by an organization grow, tasks such as data discovery and data management grow in complexity. Simply put, the more data there is, the harder it is for users such as data analysts to find what they’re looking for. A metadata hub helps manage Big Data by providing The post Datahub: Open Source Data Lake with Pardhu Gunnam and Mars Lan appeared first on Software Engineering Daily.

As the volume and scope of data collected by an organization grow, tasks such as data discovery and data management grow in complexity. Simply put, the more data there is, the harder it is for users such as data analysts to find what they’re looking for. A metadata hub helps manage Big Data by providing The post Datahub: Open Source Data Lake with Pardhu Gunnam and Mars Lan appeared first on Software Engineering Daily.

As the volume and scope of data collected by an organization grow, tasks such as data discovery and data management grow in complexity. Simply put, the more data there is, the harder it is for users such as data analysts to find what they’re looking for. A metadata hub helps manage Big Data by providing The post Datahub: Open Source Data Lake with Pardhu Gunnam and Mars Lan appeared first on Software Engineering Daily.

Part 2 of my chat with Kapil Surlaker, VP of Engg, and Head of Data at LinkedIn. We cover the topic of managing data quality at LinkedIn scale! Kapil has 20+ years of experience in data and infrastructure both at large companies such as Oracle as well as multiple startups. At LinkedIn, Kapil has been leading the next generation of Big Data Infrastructure, Platforms, Tools, and Applications to empower Data Scientists, AI engineers, App developers, to extract value from data. Kapil's team has been at the forefront of innovation driving multiple open source initiatives such as Apache Pinot, Gobblin, DataHub.

In this episode of Ventures, my guest Andrew Cronk (Co-Founder, Figment.io) and I discuss practical ways to engage with the Web 3.0 stack, how to keep up with information in the blockchain space, how to learn and teach others about crypto technologies, and where everyone is going to be storing and sharing baby photos in the future.  Visit https://satchel.works/@wclittle/ventures-episode-19 for detailed notes and links to resources (videos, articles, etc…) mentioned. You can watch this episode via video here. In this episode we cover the following:   2:30 - A quick discussion about what's been happening in the blockchain world since summer 2020, i.e. the DeFi “boom.” 4:09 - What has Figment.io been up to? Servicing two personas with three products. Coin holders and Web 3 developers, with validator nodes/staking, Hubble, and Data Hub.7:00 - Figment Learn - new product for developers to learn how to build on blockchains. 7:50 - Why do we need all these extra blockchains? Why do we need more than Ethereum?  11:23 - Regarding the question “Where do you upload your baby photos?” // What is it now within the Figment team and what will it hopefully be in the near future? 13:16 - What technology shifts are happening that are warranting the creation of these new blockchains? Trusted Execution Environments and Intel SGX, Oasis, Secret.Network. Users owning their own data. Example of the project looking at people sharing xrays/CT scans to train a model. 16:03 - Would people training these models need to be compensated with a token? 16:50 - Where are/would people's images be stored in the Web 3 stack in this example? 17:58 - What areas in the blockchain space is Andy most excited about? Where does it get his news about blockchains? Check out Messari. Privacy of data. Personal digital locker of data. 20:10 - Commentary/questions about the multidisciplinary nature of blockchains - where does Andy like to spend his time? What things are working? Speculation, DeFi like Automated Market Makers (Uniswap), and Non-Fungible Tokens (NFTs). OpenSea marketplace.     25:10 - Example of a “receipt” that could be given to consumers who buy something. 25:50 - More about Figment's new Learn product. How does it work? Who is it for? (Peer to Peer learning system)27:45 - Would people in Learn get paid in the token of the chain that is promoting content? Or what incentive mechanisms are in place?  29:48 - As a developer today, what sorts of things can I do with DataHub?30:34 - What are some examples of things I can build with NEAR? 31:55 - Will DataHub have the APIs necessary to interact with NEAR? 32:30 - Final thoughts from Andy to the Web 2 to Web 3 engineers and investors out there. Let's take back the internet.  

In this episode, I talk to Kapil Surlaker, VP of Engg, and Head of Data at LinkedIn. We cover the topic of battlescars related to Data Management. The episode is divided into two parts. In Part 1 (this episode), we cover challenges related to metadata management and data access APIs. In the next part, we deep-dive on data quality. Kapil has 20+ years of experience in data and infrastructure both at large companies such as Oracle as well as multiple startups. At LinkedIn, Kapil has been leading the next generation of Big Data Infrastructure, Platforms, Tools, and Applications to empower Data Scientists, AI engineers, App developers, to extract value from data. Kapil's team has been at the forefront of innovation driving multiple open source initiatives such as Apache Pinot, Gobblin, DataHub.

In this week's episode of 'Paisa Vaisa', Host Anupam Gupta is joined by Ashutosh Datar, Co-founder at IndiaDataHub.IndiaDataHub is an interactive data platform set up with the aim of democratizing access to public data in India. Anupam and Ashutosh talk about his background and how he started with IndiaDataHub. Ashutosh shares why the data is important, what are the sources and who are the people who should be focusing a lot more on Indian data. They also talk about how IndiaDataHub helps to solve the problem, how are they doing things differently and plans for the future. All this and a lot more on this episode of Paisa Vaisa.Tune in to find out more about finance on #PaisaVaisa with Anupam Gupta.You can know more about IndiaDataHub: (http://www.indiadatahub.com/)Twitter: @IndiaDataHub (https://twitter.com/IndiaDataHub)Linkedin: (https://www.linkedin.com/company/indiadatahub/)You can follow Ashutosh on social media:Twitter: @adatar (https://twitter.com/adatar)Linkedin: (https://www.linkedin.com/in/ashutoshdatar/)Send in your finance related queries or feedback to our host Anupam Gupta on Twitter: @b_50 (https://twitter.com/b50)You can listen to this show and other awesome shows on the IVM Podcasts app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.

In order to scale the use of data across an organization there are a number of challenges related to discovery, governance, and integration that need to be solved. The key to those solutions is a robust and flexible metadata management system. LinkedIn has gone through several iterations on the most maintainable and scalable approach to metadata, leading them to their current work on DataHub. In this episode Mars Lan and Pardhu Gunnam explain how they designed the platform, how it integrates into their data platforms, and how it is being used to power data discovery and analytics at LinkedIn.

Escucha la 3ra PARTE de la entrevista que realizamos en Nave InnovaRock al Jefe del área de Economía del Futuro del Ministerio de Economía del Gobierno de Chile, Julio Pertuzé. ¿Chile puede ser un #DataHub mundial gracias al desarrollo de la #AstroData? ¿Cuál es el impacto de la #InteligenciaArtificial y el #Blockchain? ¿Hay avances en el proyecto de Ley de #TransferenciaTecnologica?

Former NFL scout Matt Manocherian (@mattmano) gives the listeners an inside look into some of the departments here at Sports Info Solutions. Matt welcomes Senior Operations Analyst/Football Coordinator Dan Foehrenbach (@FoehrenbachD) to discuss the Ops department (1:40), Business Development Analyst Corey March (@marchmadness26) to talk about what's happening on the business side (10:29) and Research Analyst Bryce Rossler (@btrossler) to give insight into what our R&D team is working on for the upcoming year (19:12).

Former NFL Scout Matt Manocherian of Sports Info Solutions and football analytics pioneer Aaron Schatz of Football Outsiders break down all the key matchups in the game behind the game. The Rundown: Matt asks Aaron his take on Gronk threatening to retire (0:30) Look back at Week 3’s Biggest Matchups including a look at Rodgers, Brees, and Bortles (2:30) SISDataHub.com Free Trial Info (10:15) Ravens at Steelers Preview: Another Classic Showdown? (12:00) Bucs at Bears Preview: Fitzpatrick vs Winston discussion (16:30) Dolphins at Patriots Preview: Are the Dolphins for real? (27:45)