Podcasts about Software engineering

Michael Galloway (Doma and ex-Netflix) describes his process for interviewing developers to understand where his team should focus. He also explains how he thinks about the strategic value of a Platform team. Resources mentioned:  Customer Interview Guide Customer Interview Questions

Heute mit: Digital Services Act, TikTok, Diabetes, Overwatch 2 ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder IT-Consulting? Bei msg wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

Heute mit: Kernfusionsreaktor, Krisenchat, Firefly Aerospace, Pilz-Apps ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder IT-Consulting? Bei msg wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

Kutsuimme kartanolle vieraaksi merkittävän kansainvälisen uran Facebookilla eli Metalla tehneen sovellustietoturva-asiantuntijan Otto Ebelingin. Otto kertoo meille millaista on työskennellä tietoturva-asiantuntijana kaikkien tuntemassa teknologiayrityksessa, minkälainen rekrytointiprosessi oli ja millaisia työtehtäviä hänellä on ollut Metan sovellustietoturvallisuuden parissa. Keskustelemme myös keväällä 2019 tapahtuneesta WhatsAppin tietoturvaloukkauksesta, joka oli tehty NSO:n hyökkäystyökalu Pegasuksella, ja jonka tutkinnassa Otto oli mukana.  Äänijulkaisun lähdeluettelo: Vieras: Otto Ebeling https://twitter.com/loginuid  Herrasmieshakkerit Twitterissä https://twitter.com/hakkerit  Herrasmieshakkerit Youtubessa https://youtube.com/c/Herrasmieshakkerit  Erikoisjakso: Toomas Hendrik Ilves https://youtu.be/FBp66gUUglI  Cloudflare ja Kiwifarms https://blog.cloudflare.com/kiwifarms-blocked/  Äänen muokkaaminen tekoälyllä https://arstechnica.com/information-technology/2022/09/with-koe-recast-you-can-change-your-voice-as-easily-as-your-clothing/  Äänen muokkaaminen tekoälyllä - koe recast https://koe.ai/recast/  Äänen muokkaaminen tekoälyllä - resemble.ai https://www.resemble.ai/  Otto New Yorkerissa https://www.newyorker.com/magazine/2022/04/25/how-democracies-spy-on-their-citizens  Metan tuoteturvallisuus https://about.fb.com/news/2019/01/designing-security-for-billions/   The Art of Mac Malware https://taomm.org/index.html  Software Engineering at Google https://abseil.io/resources/swe-book  Assembly 2022 voittajat https://party.assembly.org/summer22/news/competition-results  M22 by p01 https://www.youtube.com/watch?v=5nb0Z16_MQY 

Digital Ocean kicks off Hacktoberfest 2022, Divam Gupta releases DiffusionBee 1.0 with “Image To Image” support, Zeno Rocha open sources Dracula UI for React, GitX gets brought back from the brink & Prerender.io engineers save a bundle by moving off AWS. Oh, and join us at All Things Open in early November!

Digital Ocean kicks off Hacktoberfest 2022, Divam Gupta releases DiffusionBee 1.0 with “Image To Image” support, Zeno Rocha open sources Dracula UI for React, GitX gets brought back from the brink & Prerender.io engineers save a bundle by moving off AWS. Oh, and join us at All Things Open in early November!

About Nathalie Lussier: Nathalie Lussier is an award-winning entrepreneur who has been making websites since she was 12 years old. She graduated with a degree in Software Engineering and a job offer from Wall Street, but she turned down this job to start her own business right out of college. As the founder of AccessAlly, […]

  Vidcast:  https://youtu.be/x__bMilMWNY   Inventive bioengineers at Georgia's Kennesaw State College of Computing and Software Engineering are developing a finger probe to  measure blood glucose levels without a blood draw, fingerstick, or even a microneedle in the subcutaneous tissue.  Named GlucoCheck, the system shines visible laser light through either finger or ear tissues and uses a smartphone to analyse the resulting images of transmitted light in order to calculate sugar levels.  Currently, the accuracy is 90%, and the researchers are tweaking their device to improve that and looking at a linkage with Amazon's Alexa ecosystem.   https://formative.jmir.org/2022/8/e38664   #glucose #diabetes #glucocheck #smartphone #alexa  

This week we turn the mics on ourselves, kind of. Lars Wikman joins the show to give us a guided tour through ID3 esoterica and the shiny new open source Elixir library he developed for us. We talk about what ID3 is, its many versions, what it aims to be and what it could have been, how our library project got started, all the unique features and failed dreams of the ID3v2 spec, how ID3v2 and Podcast 2.0 are solving the problem differently, and how all of this maps back to us giving you (our listeners) a better experience while listening to our shows.

This week we turn the mics on ourselves, kind of. Lars Wikman joins the show to give us a guided tour through ID3 esoterica and the shiny new open source Elixir library he developed for us. We talk about what ID3 is, its many versions, what it aims to be and what it could have been, how our library project got started, all the unique features and failed dreams of the ID3v2 spec, how ID3v2 and Podcast 2.0 are solving the problem differently, and how all of this maps back to us giving you (our listeners) a better experience while listening to our shows.

Today, we have Santiago Palladino, a lead developer at OpenZeppelin who has helped drive the development of OpenZeppelin's Defender product. He's also provided value as an educator for the space, and wrote a book on Ethereum for web developers in 2019. In this episode, we discuss Open Zeppelin's defender product, and it's underlying design. We also dive into the role of devops & off chain infrastructure & the future of web3 development, and explore Santiago's thoughts on the growth of the South American & Latin American crypto ecosystem.Santiago has a deep understanding of building products at the intersection of web2 & web3, and if you're interested in understanding how to build products that straddle both tech stacks - this episode is for you.OZ Defender: https://www.openzeppelin.com/defenderEthereum For Web Developers: https://link.springer.com/book/10.100...Santiago on Twitter: https://twitter.com/smpalladinoTimestamps:00:00 Intro2:26 How Santiago got involved in crypto5:58 Getting started in web3 when coming from a traditional software development background8:34 What tooling does Santiago wish existed?10:39 Open Zeppelin Defender13:58 So I've just deployed a smart contract to main net. What should I be thinking about next?17:15 How to manage security & decentralization as your project evolves22:24 The role of off chain infra in the next iteration of dapps26:05 Decentralized backend infrastructure30:24 The Defender architecture & some of Santiago's favorite design patterns used in its development35:43 How Santiago approaches API development41:05 Why multi-chain governance & account abstractions NEED to get solved 46:28 The LatAm crypto ecosystem52:19 Santiago's long term vision for the industry

Kavi Pujara (born Leicester, 1972) is a self-taught photographer. He has a BSc in Software Engineering and an MA in Screenwriting and he works as a film editor for the BBC alongside independently making personal, long-term documentary photo projects. His work has been included in the touring group exhibition Facing Britain, he was also one of the winners in the British Journal of Photography, Portrait of Britain 2020 and was the recipient of a Martin Parr Foundation photographic bursary in 2020. Two of his portraits have also this year been selected for the National Portrait Gallery's Taylor Wessing Photographic Portrait Prize exhibition and will be on display in London from 27 October - 18 December 2022. His first book project, published by Setanta Books, is This Golden Mile. Photographed against the backdrop of Brexit, the Windrush scandal, and a government intent on reducing net migration, Kavi documents Indian migration to Leicester, where he was born, exploring themes of identity, home and Britishness. An exhibition of the work will open next weekend at the Martin Parr Foundation in Bristol. On episode 188, Kavi discusses, among other things:His family historyGrowing up in LeicesterExperiences of racism growing up and on TVEscaping Leicester to do a degree and discover music and booksDiscovering cinema and film editingHis experience of screenwritingWinning the MPF bursaryHow moving back and the Brexit vote inspired This Golden MilePatriotism towards the UK amongst his parent's generation of immigrantsThe process of making the pictures for This Golden MileThe Nationality and Borders ActThe value of having the mentorship of Martin Parr……and the two most important nuggets he imparted.Referenced:Joel MeyorwitzMike MuschampTony Ray-JonesGarry WinograndDario MitidieriAsif KapadiaSmoking In Bed: Conversations with Bruce RobinsonKalpesh LathigraSathnam SangheraSian DaveyKeith Cullen Website | Instagram“The spark [for the project] came from that moment of relocating back to Leicester and within two weeks of that was the EU referendum result. Both of those moments, the personal and the political were in the space of a few weeks and I wanted to use photography to reconnect with the community I grew up in…but it was impossible to ignore the shift from that point. It was almost night and day. I really took it to heart and found it quite depressing, that societal turn towards anti-immigrant populism.”

In this episode, Willie Yao, Head of Infrastructure at Notion and former Head of Developer Infrastructure at Airbnb, provides a unique perspective on how Developer Experience teams work in hypergrowth companies. He shares how Airbnb developed a customer-first mindset internally, what it took to get Airbnb's leadership invested in that effort, and how he's approaching DevEx at Notion today. 

In this episode, we talk about optics and how Zeiss uses Markov Chains in manufacturing. We also talk about an AI engineering platform and some rumors in the chip industry.

In this episode Chris and Karis conduct a Q&A session about Launch School's new Programming Essentials Workshops, what they are why new programmers would want to attend. Karis then catches up with Launch School Alumnus Kelvin, who shares his experiences as a UK Capstone student and what it's like working as a software engineer based in the UK. The episode comes to a close with some Launch School announcements and upcoming events. to listen to the podcast click on the play button above the RSS and SHARE buttons Introduction (https://podcast.launchschool.com/programming-essentials-workshops?t=0) Workshop Q&A: What are Programming Essentials Workshops? (https://podcast.launchschool.com/programming-essentials-workshops?t=151) Workshop Q&A: Who are the workshops for? (https://podcast.launchschool.com/programming-essentials-workshops?t=350) Workshop Q&A: How do workshops differ from study sessions? (https://podcast.launchschool.com/programming-essentials-workshops?t=470) Workshop Q&A: What do I gain from attending a workshop? (https://podcast.launchschool.com/programming-essentials-workshops?t=624) Workshop Q&A: Would I learn anything new if I'm already going through the Prep Courses? (https://podcast.launchschool.com/programming-essentials-workshops?t=715) Workshop Q&A: Is it mandatory to attend a workshop for Launch School Students? (https://podcast.launchschool.com/programming-essentials-workshops?t=850) Workshop Q&A: Will there be a recording of these workshops available? (https://podcast.launchschool.com/programming-essentials-workshops?t=891) Workshop Q&A: More Information (https://podcast.launchschool.com/programming-essentials-workshops?t=931) Interview with UK Capstone Graduate Kelvin (https://podcast.launchschool.com/programming-essentials-workshops?t=1063) Annoucements (https://podcast.launchschool.com/programming-essentials-workshops?t=3285) Show Notes - Latest Programming Essentials Workshops (https://launchschool.medium.com/take-the-struggle-out-of-learning-to-program-with-3-new-workshops-9e8988204f6d) - How to navigate a recession webinar/medium post (https://medium.com/launch-school/how-to-navigate-a-recession-357f6c1a520e) - Launch School's Reddit Community (https://www.reddit.com/r/launchschool/) - Do you want to be a TA? Information Post (https://launchschool.com/posts/a1b03ff7) - Introduction to Programming with JavaScript Book with 78 new video walkthroughs (https://launchschool.com/books/javascript) - Launch School Women's Group October 9th Meetup (https://launchschool.com/posts/e6bd2e48) Fill out our form below if you have any questions about anything Launch School related whether its our prep course, Core Program, Capstone and beyond. Your question could be answered in our next episode! - Ask a Question Form (https://launchschool.com/podcast-requests)

VP of Creator Engineering Nick Tornow joins CEO and host Dave Baszucki to talk about the global creator community that builds the immersive experiences on Roblox and how we support their success. In this episode, they'll discuss the ways we're evolving creation across the three pillars of the Creator group: Roblox Studio, our content cloud, and the services that enrich our platform.

Mozilla says Firefox will continue to support current content blockers, Nabeel Sulieman thinks NATS is great and recommends you check it out, InfoQ breaks down Uber's recent security breach, Klemen Sever explained OAuth2 by drawing cute shapes & Jorge Manrubia reflects back as an aging programmer.

Mozilla says Firefox will continue to support current content blockers, Nabeel Suleiman thinks NATS is great and recommends you check it out, InfoQ breaks down Uber's recent security breach, Klemen Sever explained OAuth2 by drawing cute shapes & Jorge Manrubia reflects back as an aging programmer.

About Peter Wang:"Program maintenance is an entropy-increasing process, and even its most skillful execution only delays the subsidence of the system into unfixable obsolescence." — Frederick P. Brooks Jr., The Mythical Man-Month: Essays on Software Engineering, 1975. Simple put, all it means is once you build software and keep making changes to it. Its quality will degrade and eventually degrade to a point where it becomes unusable. Today on The One Percent Project, I am speaking to Peter Wang. Peter is the Chief Technology Officer at Buzzfeed, overseeing Product Management, Engineering, Design, and Data teams across all portfolio brands. Peter has built both consumer and enterprise products and fundraised from a diverse range of investors across industries—health (The Mighty, backed by GGVC, Upfront, and WPP Health), SaaS (Buddy Media, backed by Greylock, acquired by Salesforce), media & e-commerce (Refinery29, backed by Stripes, WPP, Scripps).Peter, in this conversation, talks about his journey as a CTO, leadership vs management, and his delegation mechanism, which Keith Rabois outlined in his essay How to be an effective executive and what has been learnt as an angel investor. Some Key Highlights:Buddy Media was acquired by Salesforce. I remember being there after it was acquired by Salesforce. And I realized that what we have built wasn't particularly the most technologically robust advanced futuristic version of it. but it was a combination of the right set of capabilities slash features that the clients need combined with the right marketing.Emotion has so much more decision-making power than we even understand.Culture is based on identity. Culture is based on values. Culture is embedded into our decision-making, even though we cannot articulate or quantify it when we talk to people.In this conversation, she talks about:00:00 Intro02:13 How does one know the role they play beyond their title?04:56 Leadership Vs Management is there a difference?06:30 As a CTO, how do you build an intelligent and practical system without being too futuristic?10:32 Delegation: Your views?13:56 Is there a difference between a CTO and a VP of engineering?17:24 90-day plan, when you kick start in a new role. The 3 Ps- Double-click on that.21:42 Is technology the secret sauce of Buzz Feed's success?24:58 What can data not do?29:38 What have you learnt as an angel investor?Links:The Mythical Man-Month: Essays on Software EngineeringKeith Rabois Essay 3: How to be an Effective Executive

This week we're talking about product development structures as systems with Lucas da Costa. The last time we had Lucas on the show he was living the text-mode only life, and now we're more than 3 years later, Lucas has doubled down on all things text mode. Today's conversation with Lucas maps several ideas he's shared recently on his blog. We talk about deadlines being pointless, trajectory vs roadmap and the downfall of long-term planning, the practices of daily stand-ups and what to do instead, measuring queues not cycle time, and probably the most controversial of them all — actually talking to your customers. Have you heard? It's this newly disruptive Agile framework that seems to be working well.

This week we're talking about product development structures as systems with Lucas da Costa. The last time we had Lucas on the show he was living the text-mode only life, and now we're more than 3 years later, Lucas has doubled down on all things text mode. Today's conversation with Lucas maps several ideas he's shared recently on his blog. We talk about deadlines being pointless, trajectory vs roadmap and the downfall of long-term planning, the practices of daily stand-ups and what to do instead, measuring queues not cycle time, and probably the most controversial of them all — actually talking to your customers. Have you heard? It's this newly disruptive Agile framework that seems to be working well.

Heute mit: Solarenergie, Trojaner Harly, Levante, G Cloud ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder Ei Ti-Consulting? Bei em es ge wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

Draft.dev provides high-quality, technical content that resonates with software developers. In this episode,  Adam Torres and Karl Hughes, Founder & CEO of Draft.dev, explore the Draft.dev story and how to create marketing content aimed at software engineers or technical audiences. Follow Adam on Instagram at https://www.instagram.com/askadamtorres/ for up to date information on book releases and tour schedule.Apply to be interviewed by Adam on our podcast:https://missionmatters.lpages.co/podcastguest/Visit our website:https://missionmatters.com/

Heute mit: Brennholz, Telefónia, Microsoft Defender, SLS ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder Ei Ti-Consulting? Bei em es ge wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

Draft.dev provides high-quality, technical content that resonates with software developers. In this episode,  Adam Torres and Karl Hughes, Founder & CEO of Draft.dev, explore the Draft.dev story and how to create marketing content aimed at software engineers or technical audiences.Follow Adam on Instagram at https://www.instagram.com/askadamtorres/ for up to date information on book releases and tour schedule.Apply to be interviewed by Adam on our podcast:https://missionmatters.lpages.co/podcastguest/Visit our website:https://missionmatters.com/

About ShinjiShinji Kim is the Founder & CEO of Select Star, an automated data discovery platform that helps you to understand & manage your data. Previously, she was the Founder & CEO of Concord Systems, a NYC-based data infrastructure startup acquired by Akamai Technologies in 2016. She led the strategy and execution of Akamai IoT Edge Connect, an IoT data platform for real-time communication and data processing of connected devices. Shinji studied Software Engineering at University of Waterloo and General Management at Stanford GSB.Links Referenced: Select Star: https://www.selectstar.com/ LinkedIn: https://www.linkedin.com/company/selectstarhq/ Twitter: https://twitter.com/selectstarhq TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by our friends at AWS AppConfig. Engineers love to solve, and occasionally create, problems. But not when it's an on-call fire-drill at 4 in the morning. Software problems should drive innovation and collaboration, NOT stress, and sleeplessness, and threats of violence. That's why so many developers are realizing the value of AWS AppConfig Feature Flags. Feature Flags let developers push code to production, but hide that that feature from customers so that the developers can release their feature when it's ready. This practice allows for safe, fast, and convenient software development. You can seamlessly incorporate AppConfig Feature Flags into your AWS or cloud environment and ship your Features with excitement, not trepidation and fear. To get started, go to snark.cloud/appconfig. That's snark.cloud/appconfig.Corey: I come bearing ill tidings. Developers are responsible for more than ever these days. Not just the code that they write, but also the containers and the cloud infrastructure that their apps run on. Because serverless means it's still somebody's problem. And a big part of that responsibility is app security from code to cloud. And that's where our friend Snyk comes in. Snyk is a frictionless security platform that meets developers where they are - Finding and fixing vulnerabilities right from the CLI, IDEs, Repos, and Pipelines. Snyk integrates seamlessly with AWS offerings like code pipeline, EKS, ECR, and more! As well as things you're actually likely to be using. Deploy on AWS, secure with Snyk. Learn more at Snyk.co/scream That's S-N-Y-K.co/screamCorey: Welcome to Screaming in the Cloud. I'm Corey Quinn. Every once in a while, I encounter a company that resonates with something that I've been doing on some level. In this particular case, that is what's happened here, but the story is slightly different. My guest today is Shinji Kim, who's the CEO and founder at Select Star.And the joke that I was making a few months ago was that Select Stars should have been the name of the Oracle ACE program instead. Shinji, thank you for joining me and suffering my ridiculous, basically amateurish and sophomore database-level jokes because I am bad at databases. Thanks for taking the time to chat with me.Shinji: Thanks for having me here, Corey. Good to meet you.Corey: So, Select Star despite being the only query pattern that I've ever effectively been able to execute from memory, what you do as a company is described as an automated data discovery platform. So, I'm going to start at the beginning with that baseline definition. I think most folks can wrap their heads around what the idea of automated means, but the rest of the words feel like it might mean different things to different people. What is data discovery from your point of view?Shinji: Sure. The way that we define data discovery is finding and understanding data. In other words, think about how discoverable your data is in your company today. How easy is it for you to find datasets, fields, KPIs of your organization data? And when you are looking at a table, column, dashboard, report, how easy is it for you to understand that data underneath? Encompassing on that is how we define data discovery.Corey: When you talk about data lurking around the company in various places, that can mean a lot of different things to different folks. For the more structured data folks—which I tend to think of as the organized folks who are nothing like me—that tends to mean things that live inside of, for example, traditional relational databases or things that closely resemble that. I come from a grumpy old sysadmin perspective, so I'm thinking, oh, yeah, we have a Jira server in the closet and that thing's logging to its own disk, so that's going to be some information somewhere. Confluence is another source of data in an organization; it's usually where insight and a knowledge of what's going on goes to die. It's one of those write once, read never type of things.And when I start thinking about what data means, it feels like even that is something of a squishy term. From the perspective of where Select Start starts and stops, is it bounded to data that lives within relational databases? Does it go beyond that? Where does it start? Where does it stop?Shinji: So, we started the company with an intention of increasing the discoverability of data and hence providing automated data discovery capability to organizations. And the part where we see this as the most effective is where the data is currently being consumed today. So, this is, like, where the data consumption happens. So, this can be a data warehouse or data lake, but this is where your data analysts, data scientists are querying data, they are building dashboards, reports on top of, and this is where your main data mart lives.So, for us, that is primarily a cloud data warehouse today, usually has a relational data structure. On top of that, we also do a lot of deep integrations with BI tools. So, that includes tools like Tableau, Power BI, Looker, Mode. Wherever these queries from the business stakeholders, BI engineers, data analysts, data scientists run, this is a point of reference where we use to auto-generate documentation, data models, lineage, and usage information, to give it back to the data team and everyone else so that they can learn more about the dataset they're about to use.Corey: So, given that I am seeing an increased number of companies out there talking about data discovery, what is it the Select Star does that differentiates you folks from other folks using similar verbiage in how they describe what they do?Shinji: Yeah, great question. There are many players that popping up, and also, traditional data catalog's definitely starting to offer more features in this area. The main differentiator that we have in the market today, we call it fast time-to-value. Any customer that is starting with Select Star, they get to set up their instance within 24 hours, and they'll be able to get all the analytics and data models, including column-level lineage, popularity, ER diagrams, and how other people are—top users and how other people are utilizing that data, like, literally in few hours, max to, like, 24 hours. And I would say that is the main differentiator.And most of the customers I have pointed out that setup and getting started has been super easy, which is primarily backed by a lot of automation that we've created underneath the platform. On top of that, just making it super easy and simple to use. It becomes very clear to the users that it's not just for the technical data engineers and DBAs to use; this is also designed for business stakeholders, product managers, and ops folks to start using as they are learning more about how to use data.Corey: Mapping this a little bit toward the use cases that I'm the most familiar with, this big source of data that I tend to stumble over is customer AWS bills. And that's not exactly a big data problem, given that it can fit in memory if you have a sufficiently exciting computer, but using Tableau don't wind up slicing and dicing that because at some point, Excel falls down. From my perspective, problem with Excel is that it doesn't tend to work on huge datasets very well, and from the position of Salesforce, the problem with Excel is that it doesn't cost a giant pile of money every month. So, those two things combined, Tableau is the answer for what we do. But that's sort of the end-all for us of, that's where it stops.At that point, we have dashboards that we build and queries that we run that spit out the thing we're looking at, and then that goes back to inform our analysis. We don't inherently feed that back into anything else that would then inform the rest of what we do. Now, for our use case, that probably makes an awful lot of sense because we're here to help our customers with their billing challenges, not take advantage of their data to wind up informing some giant model and mispurposing that data for other things. But if we were generating that data ourselves as a part of our operation, I can absolutely see the value of tying that back into something else. You wind up almost forming a reinforcing cycle that improves the quality of data over time and lets you understand what's going on there. What are some of the outcomes that you find that customers get to by going down this particular path?Shinji: Yeah, so just to double-click on what you just talked about, the way that we see this is how we analyze the metadata and the activity logs—system logs, user logs—of how that data has been used. So, part of our auto-generated documentation for each table, each column, each dashboard, you're going to be able to see the full data lineage: where it came from, how it was transformed in the past, and where it's going to. You will also see what we call popularity score: how many unique users are utilizing this data inside the organization today, how often. And utilizing these two core models and analysis that we create, you can start looking at first mapping out the data flow, and then determining whether or not this dataset is something that you would want to continue keeping or running the data pipelines for. Because once you start mapping these usage models of tables versus dashboards, you may find that there are recurring jobs that creates all these materialized views and tables that are feeding dashboards that are not being looked at anymore.So, with this mechanism by looking initially data lineage as a concept, a lot of companies use data lineage in order to find dependencies: what is going to break if I make this change in the column or table, as well as just debugging any of issues that is currently happening in their pipeline. So, especially when you will have to debug a SQL query or pipeline that you didn't build yourself but you need to find out how to fix it, this is a really easy way to instantly find out, like, where the data is coming from. But on top of that, if you start adding this usage information, you can trace through where the main compute is happening, which largest route table is still being queried, instead of the more summarized tables that should be used, versus which are the tables and datasets that is continuing to get created, feeding the dashboards and is those dashboards actually being used on the business side. So, with that, we have customers that have saved thousands of dollars every month just by being able to deprecate dashboards and pipelines that they were afraid of deprecating in the past because they weren't sure if anyone's actually using this or not. But adopting Select Star was a great way to kind of do a full spring clean of their data warehouse as well as their BI tool. And this is an additional benefit to just having to declutter so many old, duplicated, and outdated dashboards and datasets in their data warehouse.Corey: That is, I guess, a recurring problem that I see in many different pockets of the industry as a whole. You see it in the user visibility space, you see it in the cost control space—I even made a joke about Confluence that alludes to it—this idea that you build a whole bunch of dashboards and use it to inform all kinds of charts and other systems, but then people are busy. It feels like there's no ‘and then.' Like, one of the most depressing things in the universe that you can see after having spent a fair bit of effort to build up those dashboards is the analytics for who internally has looked at any of those dashboards since the demo you gave showing it off to everyone else. It feels like in many cases, we put all these projects and amount of effort into building these things out that then don't get used.People don't want to be informed by data they want to shoot from their gut. Now, sometimes that's helpful when we're talking about observability tools that you use to trace down outages, and, “Well, our site's really stable. We don't have to look at that.” Very awesome, great, awesome use case. The business insight level of dashboard just feels like that's something you should really be checking a lot more than you are. How do you see that?Shinji: Yeah, for sure. I mean, this is why we also update these usage metrics and lineage every 24 hours for all of our customers automatically, so it's just up-to-date. And the part that more customers are asking for where we are heading to—earlier, I mentioned that our main focus has been on analyzing data consumption and understanding the consumption behavior to drive better usage of your data, or making data usage much easier. The part that we are starting to now see is more customers wanting to extend those feature capabilities to their staff of where the data is being generated. So, connecting the similar amount of analysis and metadata collection for production databases, Kafka Queues, and where the data is first being generated is one of our longer-term goals. And then, then you'll really have more of that, up to the source level, of whether the data should be even collected or whether it should even enter the data warehouse phase or not.Corey: One of the challenges I see across the board in the data space is that so many products tend to have a very specific point of the customer lifecycle, where bringing them in makes sense. Too early and it's, “Data? What do you mean data? All I have are these logs, and their purpose is basically to inflate my AWS bill because I'm bad at removing them.” And on the other side, it's, “Great. We pioneered some of these things and have built our own internal enormous system that does exactly what we need to do.” It's like, “Yes, Google, you're very smart. Good job.” And most people are somewhere between those two extremes. Where are customers on that lifecycle or timeline when using Select Star makes sense for them?Shinji: Yeah, I think that's a great question. Also the time, the best place where customers would use Select Star for is that after they have their cloud data warehouse set up. Either they have finished their migration, they're starting to utilize it with their BI tools, and they're starting to notice that it's not just, like, you know, ten to fifty tables that they're starting with; most of them have more than hundreds of tables. And they're feeling that this is starting to go out of control because we have all these data, but we are not a hundred percent sure what exactly is in our database. And this usually just happens more in larger companies, companies at thousand-plus employees, and they usually find a lot of value out of Select Star right away because, like, we will start pointing out many different things.But we also see a lot of, like, forward-thinking, fast-growing startups that are at the size of a few hundred employees, you know, they now have between five to ten-person data team, and they are really creating the right single source of truth of their data knowledge through a Select Star. So, I think you can start anywhere from when your data team size is, like, beyond five and you're continuing to grow because every time you're trying to onboard a data analyst, data scientist, you will have to go through, like, basically the same type of training of your data model, and it might actually look different because the data models and the new features, new apps that you're integrating this changes so quickly. So, I would say it's important to have that base early on and then continue to grow. But we do also see a lot of companies coming to us after having thousands of datasets or tens of thousands of datasets that it's really, like, very hard to operate and onboard anyone. And this is a place where we really shine to help their needs, as well.Corey: Sort of the, “I need a database,” to the, “Help, I have too many databases,” pipeline, where [laugh] at some point people start to—wanting to bring organization to the chaos. One thing I like about your model is that you don't seem to be making the play that every other vendor in the data space tends to, which is, “Oh, we want you to move your data onto our systems. The end.” You operate on data that is in place, which makes an awful lot of sense for the kinds of things that we're talking about. Customers are flat out not going to move their data warehouse over to your environment, just because the data gravity is ludicrous. Just the sheer amount of money it would take to egress that data from a cloud provider, for example, is monstrous.Shinji: Exactly. [laugh]. And security concerns. We don't want to be liable for any of the data—and this is, like, a very specific decision we've made very early on the company—to not access data, to not egress any of the real data, and to provide as much value as possible just utilizing the metadata and logs. And depending on the types of data warehouses, it also can be really efficient because the query history or the metadata systems tables are indexed separately. Usually, it's much lighter load on the compute side. And that definitely has, like, worked well for our advantage, especially being a SaaS tool.Corey: This episode is sponsored in part by our friends at Sysdig. Sysdig secures your cloud from source to run. They believe, as do I, that DevOps and security are inextricably linked. If you wanna learn more about how they view this, check out their blog, it's definitely worth the read. To learn more about how they are absolutely getting it right from where I sit, visit Sysdig.com and tell them that I sent you. That's S Y S D I G.com. And my thanks to them for their continued support of this ridiculous nonsense.Corey: What I like is just how straightforward the integrations are. It's clear you're extraordinarily agnostic as far as where the data itself lives. You integrate with Google's BigQuery, with Amazon Redshift, with Snowflake, and then on the other side of the world with Looker, and Tableau, and other things as well. And one of the example use cases you give is find the upstream table in BigQuery that a Looker dashboard depends on. That's one of those areas where I see something like that, and, oh, I can absolutely see the value of that.I have two or three DynamoDB tables that drive my newsletter publication system that I built—because I have deep-seated emotional problems and I take it out and everyone else via code—but as a small, contained system that I can still fit in my head. Mostly. And I still forget which table is which in some cases. Down the road, especially at scale, “Okay, where is the actual data source that's informing this because it doesn't necessarily match what I'm expecting,” is one of those incredibly valuable bits of insight. It seems like that is something that often gets lost; the provenance of data doesn't seem to work.And ideally, you know, you're staffing a company with reasonably intelligent people who are going to look at the results of something and say, “That does not align with my expectations. I'm going to dig.” As opposed to the, “Oh, yeah, that seems plausible. I'll just go with whatever the computer says.” There's an ocean of nuance between those two, but it's nice to be able to establish the validity of the path that you've gone down in order to set some of these things up.Shinji: Yeah, and this is also super helpful if you're tasked to debug a dashboard or pipeline that you did not build yourself. Maybe the person has left the company, or maybe they're out-of-office, but this dashboard has been broken and you're quote-unquote, “On call,” for data. What are you going to do? You're going to—without a tool that can show you a full lineage, you will have to start digging through somebody else's SQL code and try to map out, like, where the data is coming from, if this is calculating correctly. Usually takes, you know, few hours to just get to the bottom of the issue. And this is one of the main use cases that our customers bring up every single time, as more of, like, this is now the go-to place every time there is any data questions or data issues.Corey: The first and golden rule of cloud economics is step one, turn that shit off.Shinji: [laugh].Corey: When people are using something, you can optimize the hell out of it however you want, but nothing's going to beat turning it off. One challenge is when we're looking at various accounts and we see a Redshift cluster, and it's, “Okay. That thing's costing a few million bucks a year and no one seems to know anything about it.” They keep pointing to other teams, and it turns into this giant, like, finger-pointing exercise where no one seems to have responsibility for it. And very often, our clients will choose not to turn that thing off because on the one hand, if you don't turn it off, you're going to spend a few million bucks a year that you otherwise would not have had to.On the other, if you delete the data warehouse, and it turns out, oh, yeah, that was actually kind of important, now we don't have a company anymore. It's a question of which is the side you want to be wrong on. And in some levels, leaving something as it is and doing something else is always a more defensible answer, just because the first time your cost-saving exercises take out production, you're generally not allowed to save money anymore. This feels like it helps get to that source of truth a heck of a lot more effectively than tracing individual calls and turning into basically data center archaeologists.Shinji: [laugh]. Yeah, for sure. I mean, this is why from the get go, we try to give you all your tables, all of your database, just ordered by popularity. So, you can also see overall, like, from all the tables, whether that's thousands or tens of thousands, you're seeing the most used, has the most number of dependencies on the top, and you can also filter it by all the database tables that hasn't been touched in the last 90 days. And just having this, like, high-level view gives a lot of ideas to the data platform team about how they can optimize usage of their data warehouse.Corey: From where I tend to sit, an awful lot of customers are still relatively early in their data journey. An awful lot of the marketing that I receive from various AWS mailing lists that I found myself on because I've had the temerity to open accounts has been along the lines of oh, data discovery is super important, but first, they presuppose that I've already bought into this idea that oh, every company must be a completely data-driven company. The end. Full stop.And yeah, we're a small bespoke services consultancy. I don't necessarily know that that's the right answer here. But then it takes it one step further and starts to define the idea of data discovery as, ah, you will use it to find a PII or otherwise sensitive or restricted data inside of your datasets so you know exactly where it lives. And sure, okay, that's valuable, but it also feels like a very narrow definition compared to how you view these things.Shinji: Yeah. Basically, the way that we see data discovery is it's starting to become more of an essential capability in order for you to monitor and understand how your data is actually being used internally. It basically gives you the insights around sure, like, what are the duplicated datasets, what are the datasets that have that descriptions or not, what are something that may contain sensitive data, so on and so forth, but that's still around the characteristics of the physical datasets. Whereas I think the part that's really important around data discovery that is not being talked about as much is how the data can actually be used better. So, have it as more of a forward-thinking mechanism and in order for you to actually encourage more people to utilize data or use the data correctly, instead of trying to contain this within just one team is really where I feel like data discovery can help.And in regards to this, the other big part around data discovery is really opening up and having that transparency just within the data team. So, just within the data team, they always feel like they do have that access to the SQL queries and you can just go to GitHub and just look at the database itself, but it's so easy to get lost in the sea of metadata that is just laid out as just the list; there isn't much context around the data itself. And that context and with along with the analytics of the metadata is what we're really trying to provide automatically. So eventually, like, this can be also seen as almost like a way to, like, monitor the datasets, like, how you're currently monitoring your applications through Datadog or your website with your Google Analytics, this is something that can be also used as more of a go-to source of truth around what your state of the data is, how that's defined, and how that's being mapped to different business processes, so that there isn't much confusion around data. Everything can be called the same, but underneath it actually can mean very different things. Does that make sense?Corey: No, it absolutely does. I think that this is part of the challenge in trying to articulate value that is, I guess, specific to this niche across an entire industry. The context that drives data is going to be incredibly important, and it feels like so much of the marketing in the space is aimed at one or two pre-imagined customer profiles. And that has the side effect of making customers for whom that model doesn't align, look and feel like either doing something wrong, or makes it look like the vendor who's pitching this is somewhat out of touch. I know that I work in a relatively bounded problem space, but I still learn new things about AWS billing on virtually every engagement that I go on, just because you always get to learn more about how customers view things and how they view not just their industry, but also the specificities of their own business and their own niche.I think that is one of the challenges historically, with the idea of letting software do everything. Do you find the problems that you're solving tend to be global in nature or are you discovering strange depths of nuance on a customer-by-customer basis at this point?Shinji: Overall, a lot of the problems that we solve and the customers that we work with is very industry agnostic. As long as you are having many different datasets that you need to manage, there are common problems that arises, regardless of the industry that you're in. We do observe some industry-specific issues because your data is either, it's an unstructured data, or your data is primarily events, or you know, depending on how the data looks like, but primarily because of most of the BI solutions and data warehouses are operating as a relational databases, this is a part where we really try to build a lot of best practices, and the common analytics that we can apply to every customer that's using Select Star.Corey: I really want to thank you for taking so much time to go through the ins and outs of what it is you're doing these days. If people want to learn more, where's the best place to find you?Shinji: Yeah, I mean, it's been fun [laugh] talking here. So, we are at selectstar.com. That's our website. You can sign up for a free trial. It's completely self-service, so you don't need to get on a demo but, like, we'll also help you onboard and happy to give a free demo to whoever that is interested.We are also on LinkedIn and Twitter under selectstarhq. Yeah, I mean, we're happy to help for any companies that have these issues around wanting to increase their discoverability of data, and want to help their data team and the rest of the company to be able to utilize data better.Corey: And we will, of course, put links to all of that in the [show notes 00:28:58]. Thank you so much for your time today. I really appreciate it.Shinji: Great. Thanks for having me, Corey.Corey: Shinji Kim, CEO and founder at Select Star. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry comment that I won't be able to discover because there are far too many podcast platforms out there, and I have no means of discovering where you've said that thing unless you send it to me.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.

00:00 intro3:09 How Sam got involved in crypto5:16 Multi chain maker9:36 Maker Teleport12:37 Stepping through a specific tx lifecycle with Maker Teleport, and how that compares to other message passing bridges in the space16:22 UX considerations of different cross chain message passing designs19:19 RWA on Maker21:46 Technical considerations of bringing real world assets on chain23:51 Learning how to manage *risk* as a developer28:28 What does the development process look like at Maker?32:15 What does the Maker Engineering team prioritize when considering tradeoffs?34:37 Sam's advice for thinking about smart contract security37:46 Tradeoffs with upgradable contracts42:15 How to approach naming conventions in highly visible contracts44:37 Good design patterns Sam wishes were used more often49:34 Sam's interest in MEV52:22 Sam's long term hopes for cryptoLinks:https://makerdao.com/https://twitter.com/SebVentureshttps://twitter.com/hexonaut

Dave Farley, co-author of Continuous Delivery, is back to talk about his latest book, Modern Software Engineering, a Top 3 Software Engineering best seller on Amazon UK this September. Shipping good software starts with you giving yourself permission to do a good job. It continues with a healthy curiosity, admitting that you don't know, and running many experiments, safely, without blowing everything up. And then there is scope creep…

Heute mit: Werbe-Cookies, Nvidia, GeForce, Twitter-Kauf, Code-Week ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder Ei Ti-Consulting? Bei em es ge wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

We dive into some of the ways developers can customize their keyboard with shortcuts, macros, and apps to eliminate repetitive tasks and automate the busywork that stands in the way of bigger, breakthrough innovations. Flow state can be affected by things as simple as the right lighting, so Logitech created keyboards that automatically adjust their keyboard backlighting. For those not familiar with the MX series, you can read more about the different versions, including the mechanical one, here.If you don't know about Cassidy's passion for keyboards, you can check out her website here or listen to a previous episode diving deep into the details of mechanical keyboards here.If you missed episode two, you can check it out below. In it, we chat with Marcel Twohig, Head of Design for the MX Series at Logitech, and Thomas Fritz, Associate Professor of Human Aspects of Software Engineering at the University of Zurich. We cover the research that Professor Fritz has done on flow states, the design work that Marcel and team have done to incorporate that research, and the tools that you can use to maximize your daily flow.Learn more about Paolo here.Learn more about Guilio here.

Dave Farley, co-author of Continuous Delivery, is back to talk about his latest book, Modern Software Engineering, a Top 3 Software Engineering best seller on Amazon UK this September. Shipping good software starts with you giving yourself permission to do a good job. It continues with a healthy curiosity, admitting that you don't know, and running many experiments, safely, without blowing everything up. And then there is scope creep…

The ReadME Podcast is your portal into the open source community. We'll introduce you to the people building the projects you use every day, answer your questions about tech, and guide you through the ever-changing open source landscape. We take deep dives into the trends shaping the future of technology, the culture and craft of software development, look back at the milestones that made open source what it is today, and learn from community experts. No matter where you are in your developer journey, there's something here for you.Check out more episodes, stories, and guides at The ReadME Project.  

Heute mit: ÖPNV-Ticket, Vorratsdatenspeicherung, App Store, Insight ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder Ei Ti-Consulting? Bei em es ge wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf karriere.msg.group ***SPONSOR-HINWEIS ENDE***

Robby has a chat with Professor of Computer Science at Stanford University, John Ousterhout. John founded Electric Cloud with John Graham-Cumming. Ousterhout was a professor of computer science at the University of California, Berkeley where he created the Tcl scripting language and the Tk platform-independent widget toolkit and proposed the idea of co-scheduling. Ousterhout led the research group that designed the experimental Sprite operating system and the first log-structured file system. Ousterhout also led the team that developed the Magic VLSI computer-aided design (CAD) program.When it comes to the maintainability of software, John is more interested in the design aspects of software and feels that indeed the core goal of good software design is to make it easier to maintain software and continually improve it. He explains what problem decomposition is all about and why his course on the art of software design is probably the only one of its kind in the world. Join the convo as he also talks about how to write good code comments and why they are so important, the main differences between tactical and strategic programming, how engineers can discuss long-term improvements with their boss, how his curriculum has students approach a project with two different designs before deciding which to proceed with, and so much more. Enjoy!Book Recommendations:Talent is Overrated By Geoff Colvin Helpful LinksA Philosophy of Software Design By Professor John OusterhoutTcl/TkJohn on TwitterJohn's WebpageSubscribe to Maintainable on:Apple PodcastsOvercastSpotifyOr search "Maintainable" wherever you stream your podcasts.Join the discussion in the Maintainable Discord Community

Andreas Kling's new cross-platform browser project, Dan Hollick's nerdy deep-dive on QR code tech, Stephan Dilly's Rust-based terminal UI for Git, Miłosz Piechocki's opinion on junior vs senior engineers & Divam Gupta's Tensorflow port of Stable Diffusion.

Andreas Kling's new cross-platform browser project, Dan Hollick's nerdy deep-dive on QR code tech, Stephan Dilly's Rust-based terminal UI for Git, Miłosz Piechocki's opinion on junior vs senior engineers & Divam Gupta's Tensorflow port of Stable Diffusion.

Heute mit: Taxonomie, MS teams, Elektrofähre, Susie ***SPONSOR-HINWEIS*** Der digitale Wandel ist jetzt - und er ist überall. Du bist Spezialist im Software-Engineering oder Ei Ti-Consulting? Bei em es ge wirst Du zum Wegbereiter für die digitale Transformation ganzer Branchen! In agilen Projekten eröffnen wir Kunden mit nachhaltigen Lösungen neue Wege und Dir ausgezeichnete Entwicklungsmöglichkeiten. Flexible Arbeitszeiten mit Überstundenausgleich sorgen dazu für eine gesunde Work-Life-Balance. Lerne uns kennen und bewirb Dich auf www.karriere.msg.group ***SPONSOR-HINWEIS ENDE***

This week on The Changelog we're talking about Stable Diffusion, DALL-E, and the impact of AI generated art. We invited our good friend Simon Willison on the show today because he wrote a very thorough blog post titled, “Stable Diffusion is a really big deal.” You may know Simon from his extensive contributions to open source software. Simon is a co-creator of the Django Web framework (which we don't talk about at all on this show), he's the creator of Datasette, a multi-tool for exploring and publishing data (which we do talk about on this show)…most of all Simon is a very insightful thinker, which he puts on display here on this episode. We talk from all the angles of this topic, the technical, the innovation, the future and possibilities, the ethical and the moral – we get into it all. The question is, will this era be known as the initial push back to the machine?

This week on The Changelog we're talking about Stable Diffusion, DALL-E, and the impact of AI generated art. We invited our good friend Simon Willison on the show today because he wrote a very thorough blog post titled, “Stable Diffusion is a really big deal.” You may know Simon from his extensive contributions to open source software. Simon is a co-creator of the Django Web framework (which we don't talk about at all on this show), he's the creator of Datasette, a multi-tool for exploring and publishing data (which we do talk about on this show)…most of all Simon is a very insightful thinker, which he puts on display here on this episode. We talk from all the angles of this topic, the technical, the innovation, the future and possibilities, the ethical and the moral – we get into it all. The question is, will this era be known as the initial push back to the machine?

This week is a special episode of IMPACTability® as we celebrate our 50th episode by highlighting some of the best nonprofit tips, tricks, and resources that our experts have shared with us on the podcast. We have hand-picked some of the best segments from our first fifty episodes, featuring guests who have shared their expertise in the nonprofit sector. It's IMPACTability's Greatest Hits! Highlights  Introductions 0:30 Common Donor Development mistakes. 1:30 (With Lou Traina, Senior Consultant at Soukup Strategic Solutions.) What is world class stewardship and how do you get there?  2:45 (With Mark Litzler, Director of Institutional Giving at The Cleveland Orchestra.) What are nonprofits missing with fundraising? 4:11 (With Tim Kachuriak, Founder and Chief Innovation and Optimization Officer for NextAfter.) The Who, what, when, where, and why of donors 5:10 (With Tim Sarantonio, Director of Corporate Brand at NeonOne.) Why are some nonprofits tech shy? 6:32 (With Aby Jarvis, Nonprofit Education Manager at Qgiv) New developments in fundraising 7:45 (With Nidhi Doshi, The Founder of PayBee) Benefits of donor research and tips for the field 9:30 (With Daryl Moser, Business Developement Manager at DonorPerfect ) How to get media publicity 13:45 (With Kimberly Lohman-Clapp, Founder & CEO at Golden Hour Communications, LLC) Website Identity thief's 17:00 (With Jeanne Seewald, Trademark, Copyright, and Licensing Board Certified Intellectual Property Attorney) Advice on nonprofit collaborations 20:00 (With Jayson Roa, President and Chief Executive Officer at Avow Hospice, Inc.) Risk mitigation  22:00 (Tony Olivo, Senior Vice President, Software Engineering at FlexGen®) How to handle a board, tips and tricks 26:30 (With Jamie Ross, the President and CEO of the Florida Housing Coalition.) Executive Succession Plans 28:00 (With Peggy Monson, Nonprofit Consultant at Soukup Strategic Solutions) Engage with other nonprofit professionals by joining our https://www.facebook.com/groups/impactability/ (IMPACTability® Facebook community!)  Like this episode? Subscribe to our podcast on https://podcasts.apple.com/us/podcast/impactability-the-nonprofit-leaders-podcast/id1590404155 (Apple), https://open.spotify.com/show/649fryS6H0HV5L1gncViE6 (Spotify), or your favorite podcasting app.  Leave a review: Reviews are hugely important because they help new people discover this podcast. If you enjoyed listening to this episode, please leave us a review. This podcast uses the following third-party services for analysis: Chartable - https://chartable.com/privacy

Douwe Maan's journey sounds too fantastic to be true, yet the tale that Meltano's founder shares with Jason and Patrick today is very, very real. Whether it's about doing software development by 11, joining Gitlab while juggling college responsibilities, or building his own company during today's challenging times, he has quite the story to tell. In today's episode, he speaks on Twitter, his perspective on remote work, and why data operations are a critical part of developer stacks in today's world.00:01:00 Introductions00:03:44 Hustling online at 1100:08:08 From iOS to web-based development00:10:20 How Douwe balanced school and work00:12:05 Sid Sijbrandij00:19:13 Why Twitter was integral in Douwe's journey00:21:01 What Meltano offers for data teams00:22:01 Remote work00:30:59 Gitlab's data team and what they do00:44:40 What tools do data engineers use00:47:40 Singer00:50:26 Game designer travails00:58:59 Where data operations come in01:05:12 Getting started with Meltano01:12:00 Meltano as a company01:22:09 FarewellsResources mentioned in this episode:Douwe Maan: Website: https://douwe.me/ Twitter: https://twitter.com/douwem GitLab: https://github.com/DouweM Meltano: Website: https://meltano.com/ Careers: https://boards.greenhouse.io/meltano Singer:Website: https://www.singer.io/ Mergify:Website: https://mergify.com/ If you've enjoyed this episode, you can listen to more on Programming Throwdown's website: https://www.programmingthrowdown.com/Reach out to us via email: programmingthrowdown@gmail.comYou can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon ★ Support this podcast on Patreon ★

Programming is so broad and always advancing. So how do you keep up with a field that is seemingly changing everyday? Layne Moseley is your guy! In this episode he shares why he walked away from studying Computer Science at college and found his way back into the field when he discovered app development with the release of the first iPhone. From there, he went on to work for a tech start-up company, Crumbl Cookies and Snapchat! Learn how to prepare for interviewing for jobs in programming and what resources he uses to stay current on fields in tech like Artificial Intelligence, App Development and Software! P2Become Instagram: https://www.instagram.com/p2become/ P2Become TikTok: https://www.tiktok.com/@p2become

Jacob Kaplan-Moss writes up a hot take on software quality, Wilfred Hughes creates the diff tool he's always wanted, Josh Collinsworth thinks React is only great at being popular, Jetpack's Devbox project looks pretty cool & James Williams sets out to find the shortest URLs on the internet. Oh, and chapters are here!

Ella Ehrlich has been a developer at Jane Street for close to a decade. During much of that time, she's worked on Gord, one of Jane Street's oldest and most critical systems, which is responsible for normalizing and distributing the firm's trading data. Ella and Ron talk about how to grow and modernize a legacy system without compromising uptime, why game developers are the “musicians of software,” and some of the work Jane Street has done to try to hire a more diverse set of software engineers.You can find the transcript for this episode  on our website.Some links to topics that came up in the discussion:EG, The League of Legends team that Ella is a huge fan of.Apache Kafka, the message bus that Gord migrated to.Some of the various sources of symbology you have to deal with when normalizing trading data. (Really, there are too many sources to list here!)A list of Jane Street's recruiting Programs and Events, including INSIGHT, which focuses on women, and IN FOCUS, which focuses on historically underrepresented ethnic or racial minorities.

Jacob Kaplan-Moss writes up a hot take on software quality, Wilfred Hughes creates the diff tool he's always wanted, Josh Collinsworth thinks React is only great at being popular, Jetpack's Devbox project looks pretty cool & James Williams sets out to find the shortest URLs on the internet. Oh, and chapters are here!

This week we're joined by Jason Bosco, co-founder and CEO of Typesense — the open source Algolia alternative and the easier to use ElasticSearch alternative. For years we've used Algolia as our search engine, so we come to this conversation with skin in the game and the scars to prove it. Jason shared how he and his co-founder got started on Typesense, why and how they are “all in” on open source, the options and the paths developers can take to add search to their project, how Typesense compares to ElasticSearch and Algolia, he walks us through getting started, the story of Typesense Cloud, and why they have resisted Venture Capital.

About Femi:Grounded in the fact I am the 1st Generation American of parents from Barbados & Nigeria. Growing up on the northwest side of Milwaukee.  I've never been scared to start over.  I've seen hardship and even through hard times expectations remained high.  Employing many lessons learned in integrity & tenacity in tandem with unwavering curiosity, creativity and grit; I navigated the challenges of being a black male growing up in Milwaukee and emerged to become a successful Computer Engineer.  Demonstrating success working in computer software development, software Consulting and now Sales Engineering. Tap in with Femi @0luvizion across all social media platforms."The Playbook" is a series of episodes that are geared toward providing specific step-by-step instructions on how to pursue a given career path. Please note that "The Playbook" series is separate and apart from our regularly scheduled content.Welcome to the ScholarChip$ Podcast hosted by Tone Gaines and Larry Alexander. Larry is a transactional attorney at a Fortune 100 Company. Tone is a Corporate M&A attorney at a large law firm in Chicago. But more importantly, both Larry and Tone are Black men from the inner city of Milwaukee, Wisconsin. The duo started the ScholarChip$ podcast in hopes of inspiring the next wave of scholars. Discussions in this podcast are for general information and entertainment purposes only and should not be considered legal advice. Always consult a lawyer for your individual circumstances.

Martin Heinz thinks you should be using Python's walrus operator, you probably believe some falsehoods about email, Carlos Fenollosa threw in the towel after self-hosting his email for 23 years & Leon is an open source personal assistant that can live on your server.

Today, we are releasing the full interview of one of our favorite episodes: Dan's 2021 conversation with engineers-turned-authors, Hyrum Wright & Titus Winters.As two of the most senior staff engineers at Google, both guests brought a deep understanding of software engineering to the show: Hyrum is semi-famous as the "Hyrum" of Hyrum's Law; while Titus is responsible for managing 250 million lines of code and over 12,000 developers.In their brilliant book Software Engineering at Google: Lessons Learned from Programming Over Time, Hyrum & Titus explore the engineering practices that make one of the largest codebases in the world sustainable and healthy. Show NotesRegister for Interact on October 25thLearn about the power of Continuous MergeDownload their book: Software Engineering at Google: Lessons Learned from Programming Over TimeWant to try LinearB? Book a LinearB Demo and use the "Dev Interrupted Podcast" discount code.Join our Discord Community