Podcasts about data whisperer

In this episode of the Data Malarkey Podcast, host Sam Knowles welcomes Scott Taylor, The Data Whisperer, to break down why data storytelling is the missing business skill in the world of AI, analytics, and business intelligence. Scott shares why he believes in Truth Before Meaning, the idea that businesses need clean, structured data before they can extract meaningful insights. He also explains why tech jargon is holding the data industry back, why business leaders don't care how data works, and how he's making the world of data more relatable through Data Puppets. What You'll Learn in This Episode: The biggest mistakes data leaders make when presenting to executives Why data management is the foundation for AI success How to tell data stories that business leaders actually understand The origins of Data Puppets and why humour matters in data Resources Mentioned: Scott Taylor's book: Telling Your Data Story (Amazon) Scott's YouTube Channel: The Data Whisperer Data Puppets: www.datapuppets.com Scott's 2024 Big Data London keynote – “Data is the new bullsh*t” www.youtube.com/watch?v=5LRVF-1nGPQ “The Little Red Data Hen” www.youtube.com/watch?v=OBFwiGN3XK0 The DataVengers: www.datacated.com/datavengers Data Storytelling Scorecard: data-storytelling.scoreapp.com Join the Conversation: Take the Data Storytelling Scorecard: data-storytelling.scoreapp.com Follow the podcast for more insights on data, storytelling, and business communication. Connect with Us: Scott Taylor: LinkedIn | MetaMeta Consulting  Sam Knowles:  https://insightagents.co.uk Rate, Review, and Follow! If you enjoyed this episode, rate and review us on Apple Podcasts, Spotify, or YouTube. It helps us reach more people who care about data and storytelling!  

Data is such an important and growing aspect of the tech world. And it's really important to get executive buy in to support the projects you want to do. So in this episode we're talking about Data Storytelling. Scott Taylor aka The Data Whisperer is an industry veteran, regular keynote speaker and successful author. The Tech World Human Skills Podcast is produced by people in the tech world for people in the tech world. Learn tips and best practices that help you thrive in your career. Show Links Ben Pearce LinkedIn - https://www.linkedin.com/in/benpthoughts/ Tech World Human Skills Home - www.techworldhumanskills.com Scott Taylor Linked In - https://www.linkedin.com/in/scottmztaylor/ Meta Meta Consulting - https://www.metametaconsulting.com/

How can storytelling transform the way we communicate data and create meaningful impact in the business world? By focusing on the “why” behind the numbers, data professionals can bridge the gap between technical insights and business leadership.In this episode, we're joined by Scott Taylor, widely known as The Data Whisperer and founder of Meta Meta Consulting. A full-time content creator in the data space, Scott shares how he built his reputation as a master communicator and advocate for storytelling in the data industry.Scott highlights the growing opportunities for personal branding and content creation within the data community, encouraging professionals to embrace these avenues to stand out. He advises newcomers to the field to prioritise developing storytelling skills, calling it a “superpower” that can set them apart and drive their success.With his passion for data, deep expertise in communication, and a mission to empower professionals through his work at Meta Meta Consulting, Scott offers invaluable insights into becoming more effective and impactful in the world of data. Whether you're a seasoned data expert or just starting your journey, this conversation will inspire you to approach data storytelling with fresh purpose and creativity.0:00 Introduction2:01 Advice from Scott Taylor's Book on Data Storytelling4:31 Challenges in Communicating Data Value7:54 The Importance of Storytelling in Data Management11:06 The Evolution of Data Management and Its Challenges16:14 The Role of Data in Business and Consumer Contexts23:46 The Impact of Storytelling on Data Management Success32:28 The Role of Public Speaking in Data Leadership50:34 The Future of Data Management and Trends52:47 Quick Fire Data: Myths, Recommendations, and AdviceTo learn more about Scott head to https://www.metametaconsulting.com/Welcome to “Let's Talk Data”, a deep dive into the transformative realm of data with the trailblazers of this disruptive industry.Your host Emma Crabtree explores the latest trends and developments in the data sector, while also delving into the personal stories of these data pioneers.They reveal how they harness data, not just in business, but in shaping their everyday lives, from optimising daily routines to making data-informed decisions. You'll hear about their motivations, role models, and how they plan to use their position to innovate, inspire and influence change.Many companies today are still missing the golden opportunity to unlock true potential with their data. Our conversations will shed light on this untapped potential as well as the pivotal role that data professionals play in driving progress.“Let's Talk Data” is your go-to source for inspiration and knowledge, providing a front-row seat to the future of data-driven insights and innovations.

Social Handles:LinkedIn Personal: https://www.linkedin.com/in/kruti-lehenbauer/LinkedIn Business: https://www.linkedin.com/company/analytics-tx-llc/Twitter/X: https://twitter.com/analyticstxYouTube: https://youtube.com/@AnalyticsTXFacebook: https://www.facebook.com/analyticstxInstagram: https://www.instagram.com/datawhispering/ ***********Susanne Mueller / www.susannemueller.biz TEDX Talk, May 2022: Running and Life: 5KM Formula for YOUR Successhttps://www.youtube.com/watch?v=oT_5Er1cLvY 700+ weekly blogs / 400+ podcasts / 26 marathon races / 5 half ironman races / 2 books / 1 Mt. Kilimanjaro / 1 TEDx Talk / 1 Ironman….

Policies were made to be broken. Users don't like to read instructions. And ChatGPT is a giant black box. What's the worst that could happen? Find out on this episode of DM Radio, as Host @eric_kavanagh interviews three DataVengers who will speak at the Data Universe Conference in New York next week: Kate Strachnyi of DATAcated, Scott Taylor, the Data Whisperer, and George Firican of LightsOnData! And be sure to stop by the DataVengers Booth!

Shhh...do you hear that? It's the Data Whisperer. And he's here to tell a story: A data story. He'll disclose some hard-won truths. He'll philosophically approach the idea of truth before meaning. There may even be...data puppets.

Shhh...do you hear that? It's the Data Whisperer. And he's here to tell a story: A data story. He'll disclose some hard-won truths. He'll philosophically approach the idea of truth before meaning. There may even be...data puppets.

Dive into data storytelling, puppets, musicals, comedy, and master data management with the Data Whisperer himself, Scott Taylor. Learn how Scott blends decades of experience with innovative techniques to make complex data stories accessible and engaging. SHOWPAGE: www.ninjacat.io/blog/the-neverending-data-story  © 2024, NinjaCat

In this extraordinary episode, we're joined by none other than Scott Taylor, the Data Whisperer and mastermind behind the ingenious Data Puppets.Join us as we showcase some delightful Data Puppet video clips and uncover the story behind this creative journey.Scott's innovative approach to data education has taken the industry by storm, making complex concepts accessible to all. From the serious side of creative development to the sheer joy of blending data with puppetry, this episode is a rollercoaster of insights and inspiration.

Data storytelling. One of the hottest non-tech trends in the tech space, telling your data story has been critical for data management leaders to secure stakeholder involvement and executive commitment.But why is data storytelling so important in today's world? And how can people get started? In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Scott Taylor, Data Whisperer, DataVenger and Principal Consultant at MetaMeta to discuss:Data storytelling and how to get startedThe data communityWhy data is the new bullsh*t

Scott Taylor (aka the Data Whisperer) is an OG in data content, speaking, and storytelling. He's been keynoting data events since the 1990s and keeps sharpening his game. Scott is someone I look up to, and I always enjoy our chats. LinkedIn: https://www.linkedin.com/in/scottmztaylor/ Website: https://www.metametaconsulting.com/ YouTube: https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw (Note - there's a very slight interruption with our internet connection at the 35 minute mark) ----------------------- If you like this show, give it a 5-star rating on your favorite podcast platform. Purchase Fundamentals of Data Engineering at your favorite bookseller. Subscribe to my Substack: https://joereis.substack.com/

The final episode of Season 2 and my guest is none other than Scott Taylor - the data whisperer! Yep this is the final episode of Season 2 of 66 questions. Scott and I had a lot of fun making this episode as the season finale! I've had a hoot doing this season and finishing it with much laughter and comedy moments was probably the best way to go! So enjoy listening to Scott do his thing and please do like, share, and comment. Tell everyone you know! Behind every data leader there is a person and here is Scott unplugged.

Debbie Reynolds, “The Data Diva” talks to Scott Taylor, The Data Whisperer, and Principal Consultant MetaMeta Consulting. We delve into Scott's background in the field of privacy and how it has impacted his business, the rapidly increasing amount of data and its impact, the recognition that data privacy is not a new issue, the crucial role of data insight, quality, and trust in decision making, and Scott's book "Telling Your Data Story". We also touch upon the importance of information governance, the integration of data privacy into business practices, the dangers of complacency in privacy, the management's incorrect focus on data, the limitations of technology in solving data problems, the need to ask the right questions, and Scott's vision for the future of Data Privacy.Get Scott's Book:Telling Your Data Story - Data Storytelling for Data Management 20% off with code: DATAWHISPERERhttps://technicspub.com/data-storytelling/Support the show

Learn all about how The Data Whisperer uses data to solve the world's problems, one data story at a time.

What happens when you get two modern data experts in a room to talk shop over a beer? Let's find out!In celebration of the 20th episode of the podcast, Malcolm sits down again with the guest who kicked things off on Episode 1 of the CDO Matters podcast, Scott Taylor (aka. The Data Whisperer). Malcolm hosted Scott for a casual chat in his Florida home to catch up and talk all things data over drinks. Throughout the episode, the two discuss current trends, issues and observations about the data space.Topics of conversation include:• A retrospective of the CDO Matters podcast• Data storytelling and finding a unique voice within the industry• Lessons and tips for current and aspiring CDOs• The importance of data messaging• Upcoming events and appearancesAnd so much more!Key Moments[3:00] Looking Back at Episode 1 on Data Storytelling[10:00] Bringing a Unique Voice to the Data Conversation[15:30] The Failure in Data Management Consulting Today[23:12] Lessons for CDOs from Scott and Malcolm's Travel Consulting[28:05] Reformatting Data Message Delivery[31:15] Misconceptions about Organizational ‘Culture Change'[35:50] Separating Data from Analytics: Analytical vs. Operational[41:06] Scott's Upcoming Data Plans and AppearancesKey Takeaways Delivering a Data Narrative in a Unique Voice (10:00)“I hope I am bringing a unique voice to the [data] space. That was the whole goal [with the podcast]. One of the reasons why I wanted Scott to be guest number one and why I'm thrilled that he's guest number 20…I wanted this to be a different voice. I've been in the data space for a long time. A lot of what I see…is the same old messaging over and over and over…the conclusion that I came to is that the way we're delivering the message is wrong…what I was seeing from Scott was him delivering the message in a very different way through storytelling.” — Malcolm HawkerSeparating Data and Analytics: Operational vs. Analytical Use Cases (38:20)“Going back to analytical versus operational, I don't know how you throw those into siloes. It doesn't make any sense to me. What I see happen is when you give the keys to domains or groups or functions or departments to come up with their own analytics…they'll create their own rules and their own data definitions and their own data quality rules and dashboards…and maybe that freedom is good, but then you have to operate cross-functionally to move a contract out of sales and into finance or move the product from manufacturing into marketing…and then, what happens?” — Malcolm HawkerSelling Leadership on a Data Solution (31:20)“When you're going for funding [on a data project] and you're back at saying that some version of this latest, greatest thing is going to fix all of the problems that I told you we were going to fix…the same as the last time. And so you've got, I believe on the business side, a certain amount of cynicism and weariness…And I don't think it helps that, as data people, we come barging in there talking with selective amnesia…pretending that we never said that our previous approach would solve the problem.” — Scott TaylorAbout Scott TaylorScott Taylor, also known as The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of master data and proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” At MetaMeta Consulting he works with Enterprise Data Leadership teams and Innovative Tech Brands to tell their data story.EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedInFollow Scott Taylor on LinkedInVisit MetaMeta Consulting's website

https://www.patreon.com/datameshradio (Data Mesh Radio Patreon) - get access to interviews well before they are released Episode list and links to all available episode transcripts (most interviews from #32 on) https://docs.google.com/spreadsheets/d/1ZmCIinVgIm0xjIVFpL9jMtCiOlBQ7LbvLmtmb0FKcQc/edit?usp=sharing (here) Provided as a free resource by DataStax https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio (AstraDB); George Trujillo's contact info: email (george.trujillo@datastax.com) and https://www.linkedin.com/in/georgetrujillo/ (LinkedIn) Transcript for this episode (https://docs.google.com/document/d/1cIQo0dVDI2rKqYkzVJvhj-ipjd3t7kC66aWyGDmRBk8/edit?usp=sharing (link)) provided by Starburst. See their Data Mesh Summit recordings https://www.starburst.io/learn/events-webinars/datanova-on-demand/?utm_campaign=starburst-brand&utm_medium=outbound&utm_source=&utm_type=&utm_content=dmradiodnvid&utm_term= (here) and their great data mesh resource center https://www.starburst.io/info/distributed-data-mesh-resource-center/?utm_campaign=starburst-brand&utm_medium=outbound&utm_source=&utm_type=&utm_content=dmradiodmcenter&utm_term= (here). You can download their Data Mesh for Dummies e-book (info gated) https://starburst.io/info/data-mesh-for-dummies/?utm_campaign=starburst-brand&utm_medium=outbound&utm_source=&utm_type=&utm_content=dmradiodnvid&utm_term= (here). Scott's LinkedIn: https://www.linkedin.com/in/scottmztaylor/ (https://www.linkedin.com/in/scottmztaylor/) Scott's Website: https://www.metametaconsulting.com/ (https://www.metametaconsulting.com/) Scott's Book: https://technicspub.com/data-storytelling/ (https://technicspub.com/data-storytelling/) (save 20% off with code DATAWHISPERER) Scott's YouTube playlist: https://www.youtube.com/playlist?list=PLashWxBySOAOKUtvn2NTBQeENJTLB8NoS (https://www.youtube.com/playlist?list=PLashWxBySOAOKUtvn2NTBQeENJTLB8NoS) In this episode, Scott interviewed Scott Taylor AKA the Data Whisperer. From here forwards, "Scott T" will be used to represent Scott Taylor to differentiate from your host. It's also important to note Scott T differentiates 'data management' from 'analytics', so things like data governance and infrastructure fall under data management. Some key takeaways/thoughts from Scott T's point of view: To actually reliably successfully obtain funding for data management initiatives, you need to articulate the value of the work to the business - why does this matter? Storytelling is key. The quickest way to lose your shot at securing funding for data initiatives is to focus on the how instead of the why. Most execs do not care at all how it gets done. They hired you, the data leader, to handle that. To get funding, focus your messaging on tying your data strategy and proposed data initiatives to the business strategy. Why does this matter - how will this drive the business strategy forward? Be prepared for cynicism from the business side - many have heard about how this or that data/technology initiative will be the silver bullet for far too long. Digital transformation is an enormous opportunity to change how your organization deals with data. Use that as a good point of leverage for funding your data management - it's a necessary foundation for a digital enterprise. 'Story' is about constructing a narrative and 'telling' is about effectively communicating. So storytelling is about effectively communicating what is the target outcome and why will this drive value. Data storytelling is an art, not a science. You need practice to get good at it. Don't make your 'practice' be overly high stakes. Talk to a lot of folks on your side to hone your talking points. You don't publish the first draft of a book do you? Find your editors. Focus on empathy and listening to find your audience's aspirations and pain points. Then tie your messaging about your data initiatives to those...

Recent Episodes: Season 1 | Episode 3| Quarter 3, 2022 Scott Taylor on the value of Data Storytelling for Better Data Management Episode summary: In this episode, the host Nupur Gandhi is joined by the witty and the talented storyteller, Scott Taylor also touted as the Data Whisperer. He captivates you with valid analogies and funny witticisms' as he shares his career journey as a corporate professional in Nielsen and Dun & Bradstreet. He candidly shares his experiences, mistakes, challenges and learnings that have helped pave the way for him as a content creator and ultimately to being a solopreneur as a 'Data Whisperer'. You do not want to miss his practical tips and tricks spilled all over the podcast, on Data Storytellying, engaging the audience and garnering support from senior management. Key Takeaways: If you break Storytellying into three parts, there's the data part, there's the story part, which is how you put that narrative together and there's a telling part. How do you present it? Think about: Are you capturing people's attention? Do they care? And really focus on the message that we're trying to deliver. One personal favorite technique used as a part of storytelling is to is how few words can I use? Reflect on Truth before meaning and find the truth in the data, before sharing the meaning. Tips on securing support of higher management: You got to be ready to present in a compelling way. Your first couple of minutes are the most important. Better understand your business and you better know what your executives are already talking about. If you plan to talk about a data program, you have to show why that work will enable the strategic intention of the enterprise. Where is your company going and why does data help you get there? Be okay to demonstrate courageous leadership, if you believe strongly about a topic, even if your thought is not conventional or popular one. Golden rule of data, is do unto your data as you would have it do unto you. Always remember if you have an initiative, no matter what it is, that's based on technology, hardware, software, data. If you have data, you need data management. Data Management is macro trend, agnostic. Don't talk about what you will deliver. Deliver it and then showcase the results. A lot of it is the positioning, a lot of it's in how we articulate it, which is part of what storytelling is all about. Leverage 1 min with a CEO: Start with some of the big things that are already on their mind. Have that in your head. Be fluent in what your business is trying to do. And if you're looking for where those initiatives are, what the vision of your company is, look at your own annual report or your own company strategy statement. Also be ready for a yes and when you get the yes, move on. Learn your business as a data leader and you will find opportunities and potentially funding. More about the guest, Scott Taylor: Scott Taylor, more popularly known as The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” As Principal Consultant for MetaMeta Consulting he helps Enterprises and Tech Brands tell their data story.

In this episode, Seth and Chris talk with Scott Taylor, the "Data Whisperer" about telling stories about data management.Highlights:2:00 Data Whisperer origin story9:30 Translating complex dry material into a story that resonates11:30 Why master data is the most important data and how to help execs understand it18:15 Bad data + AI = AS (Artificial Stupidity)22:30 Every system demos perfectly26:25 Don't say "data quality"27:30 Definition of digital transformation32:00 Ugly babies and the reality of bad data38:30 About the book, "Telling Your Data Story" 99% buzzword free (coupon code in show notes)47:00 Data management is macro trend agnostic49:00 What's next - more puppets and dad jokes52:00 Influencing the next generation of data managersLinks:LinkedIn Profilehttps://www.linkedin.com/in/scottmztaylor/Website www.MetaMetaConsulting.comBOOKTelling Your Data Story  - Data Storytelling for Data Management20% off with code: DATAWHISPERER (publisher site only)https://technicspub.com/data-storytelling/Top ContentToo Much Tech Talk?  (A puppet service announcement)The Little Red Data Hen - A Cautionary TaleConnecting Data Management to the Essence of Your BusinessData Has Got to Move to Have ValueThe Super Hero Adventures of **Master Data** Scott Taylor - The Data Whisperer YouTube Channel Thanks to our sponsors:Marketing AI InstituteCMSWireEarley Information ScienceAI Powered Enterprise Book

August 1, 2022 Episode 21: The Importance of Data Management with Scott Taylor, The Data Whisperer In this episode Scott Taylor, The Data Whisperer and Principal Consultant for Meta Meta Consulting, talks about how to tell a better story so that your company can focus on the importance of data management. Scott also talks about the importance of knowing your business and his experience working in consulting.     0:00 Intro  0:53 What Scott does  4:25 Scott's favorite part of his job  6:24 Scotts career path from History to data management  11:15 What education do you need to be a data scientist  14:06 Consulting  18:09 Improving your communication  19:40 Using LinkedIn for Business  20:51 Resources for Data Scientists  22:47 Scotts advice for new data scientists  24:14 Outro    Resources:  Scott's YouTube Scott's Book Telling Your Data Story MetaMeta Consulting People to follow  Kate Strachnyi Andrew Jones Dave Langer Susan Walsh George Firican Data science resources  https://www.kdnuggets.com/  Start with Why book  Communication resources  110 Techniques of Communication  Using Video to Build Relationships   Learn more about data science and stay up to date with the podcast by connecting with us on LinkedIn. https://www.linkedin.com/school/buffa... Interested in a career in data science? Visit https://dataanalytics.buffalostate.edu/ to learn more.

There's always a story behind everything. At the end of the day, leadership wants to know the overall narrative that goes with your data. CDOs need to add storytelling to their resume!In the inaugural episode of the CDO Matters Podcast, Profisee Head of Data Strategy and former Malcolm Hawker speaks to his former colleague, “The Data Whisperer” Scott Taylor, on the art and science of data storytelling — and how to frame the critical importance of trusted data in a way that resonates with business leaders.In his years of consulting, speaking and writing on all things master data and data management, Scott has developed a unique storytelling approach to make sense of complex ideas in ways that prompt business leaders to action and get funding for enterprise data projects.Malcolm and Scott discuss why business leaders don't care about the technical or dogmatic approach to data management and CDOs can hone their storytelling abilities to deliver a pitch with passion, clarity and effectiveness. They push past the buzzwords, trends and stodgy approaches to data management and stress the importance of starting any data initiative pitch with “why.”And despite the reality that most business leaders will never care about data for its own sake, they close the conversation with a sense of optimism and hope about the future of high-quality, trusted data in the marketplace.Key Moments01:30 CDO Matters: A new approach to data storytelling05:20 Creating a compelling narrative for business leaders05:52 What to avoid starting with — and leading with ‘why'08:30 The 3 Vs of Data Storytelling10:15 Honing data storytelling abilities13:50 Leading your pitch with Passion16:03 Should you try changing the data culture?17:52 Forget the dogmatic approach to data management21:14 Data is fuel, not the exhaust12:16 Showing vulnerability as a data leader22:52 The importance of a consistent data philosophy23:36 Why businesses don't care about data quality24:42 Optimism about the future of data managementKey TakeawaysCreating a Compelling Narrative around Data Initiatives (4:43-5:32)“There's this idea you have to create a compelling narrative that the business would understand so they can really support and literally fund the work that was so important in the data management space…” - Scott TaylorHoning Your Storytelling Abilities (10:21-11:05)“I think everybody is a born storyteller...they've got to be human and to be successful in business...you've got to be able to convince someone of the benefits of the offer or articulate some kind of need.” - Scott TaylorVulnerability as a Data Leader (12:16-12:54)“These are lessons for CDOs as well, and one of them is vulnerability...if you are in front of a large group, particularly technology folks, you say, ‘Here are the things that I can't do'...” - Malcolm Hawker The Unique Impact of Data Professionals (17:00-17:49)“There's not another group [data professionals] in an organization that can bring value to every other part of the company…financing, sales, operations…” – Scott TaylorForget the Dogmatic Approach to Data Management (17:52-18:40)“If I'm being told I need to change the [data] culture…and what don't you understand about how important data is, if I am managing a supply chain or selling something, that doesn't really resonate with me…” – Malcolm HawkerAbout the GuestScott Taylor, also known as The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of master data and proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” At MetaMeta Consulting he works with Enterprise Data Leadership teams and Innovative Tech Brands to tell their data story.EPISODE LINKS & RESOURCES:Follow Scott on LinkedInScott's 2020 book, “Telling Your Data Story”Scott's ‘Data Whisperer' explainer videos

Kerry Straine is CEO and founder of Straine Dental Management and Straine Dental Consulting. They work with over 280 practices on a daily basis and have 38 practices under management with a significant pipeline of high performing practices. Kerry began his career in public accounting before becoming the “accidental dental” consultant. In this episode he discusses his new style of DSO and how they plan to grow to 150 locations by 2025.  Austin and Kerry also talk about the mindset needed to scale organization and where the economy is going from here.Get in touch: kerry@straine.com or his mobile 916-765-7200.If you need help finding the perfect location or your ready to invest in commercial real estate, email us at podcast@leadersre.com. Sign up for a FREE vulnerability analysis and lease renewal services View our library on apple podcasts or REUniversity.org.Connect on Facebook.Commercial Real Estate Secrets is ranked in the top 50 podcasts on real estate 

Right now, I reckon both ScoMo and Albo would do just about anything to have a crystal ball to show them Saturday's election results.  But such things don't exist. But, we do have the closest thing, and that's big data and artificial intelligence. And they're saying one thing loud and clear - people are fed up with the major parties and the leaders throwing insults at each other and are instead turning Teal. So much so, some analysts, like my next guest experienced economist and data strategist from maven Data, otherwise known as “The Data Whisperer”, Elisa Choy, are referring to this election as “Independents Day”.      See omnystudio.com/listener for privacy information.

Artificial intelligence. The catch-all term defines the machines that can mimic and display sentient cognitive skills such as learning and problem-solving. A key part of modern technology, the advancements of AI indicate just how far the human race has come.  AI can be used by businesses to interpret and use massive volumes of data. In this third episode of a three-part EM360 podcast series with Findability Sciences, Data Whisperer and Analytics Expert, Christina Stathopoulos speaks to the company's Founder and CEO Anand Mahurkar, as the pair explore: Getting the most out of wide data Bringing the power of AI to traditional automation solutions Calculating ROI for AI projects

Artificial intelligence. The catch-all term defines the machines that can mimic and display sentient cognitive skills such as learning and problem-solving. A key part of modern technology, the advancements of AI indicate just how far the human race has come. AI can be used by businesses to interpret and use massive volumes of data. In this third episode of a three-part EM360 podcast series with Findability Sciences, Data Whisperer and Analytics Expert, Christina Stathopoulos speaks to the company's Founder and CEO Anand Mahurkar, as the pair explore: Getting the most out of wide data Bringing the power of AI to traditional automation solutions Calculating ROI for AI projects

Want to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next.AbstractMaking Data Simple Podcast is hosted by Al Martin, WW VP Account Technical Leader IBM Technology Sales, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.This week on Making Data Simple, we have Scott Taylor. Scott is the Data Whisperer, a thought leader, consultant on the strategic value of data management, Principal Consultant of MetaMeta Consulting and he practices data evangelism as a service. Scott discusses helping people understand the value and strategic importance of simple data.Show Notes1:25 – Scott's back ground4:30 – Does Scott talk to data?5:20 – How long has Scott been in data?6:50 - Data Management13:12 - Data Story telling17:05 – Structured data25:08 - Core manifesto 25:48 – Bad data ideasConnect with Scott TaylorScott Taylor - LinkedInScott Taylor - TwitterScott Taylor – The Data Whisperer YouTube channelConnect with the TeamProducer Kate Brown - LinkedIn.Producer Steve Templeton - LinkedIn.Host Al Martin - LinkedIn and Twitter.

Want to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next.AbstractMaking Data Simple Podcast is hosted by Al Martin, WW VP Account Technical Leader IBM Technology Sales, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.This week on Making Data Simple, we have Scott Taylor. Scott is the Data Whisperer, a thought leader, consultant on the strategic value of data management, Principal Consultant of MetaMeta Consulting and he practices data evangelism as a service. Scott discusses helping people understand the value and strategic importance of simple data.Show Notes1:25 – Scott's back ground4:30 – Does Scott talk to data?5:20 – How long has Scott been in data?6:50 - Data Management13:12 - Data Story telling17:05 – Structured data25:08 - Core manifesto 25:48 – Bad data ideasConnect with Scott TaylorScott Taylor - LinkedInScott Taylor - TwitterScott Taylor – The Data Whisperer YouTube channelConnect with the TeamProducer Kate Brown - LinkedIn.Producer Steve Templeton - LinkedIn.Host Al Martin - LinkedIn and Twitter.

Listen in on a delightful perspective on how to implement Data Science starting from a Data Management strategy standpoint. Scott Taylor, the “Data Whisperer” and a public speaker and published author in Data Management, has helped multinational and global executives obtain funding for their data science and data management projects from senior leaders and investors in their enterprises. We introduce his powerful approach on storytelling, including Scott's technique of bringing vocabulary, voice, and vision as a prelude to successful data management and data science real applications.

Listen in on a delightful perspective on how to implement Data Science starting from a Data Management strategy standpoint. Scott Taylor, the “Data Whisperer” and a public speaker and published author in Data Management, has helped multinational and global executives obtain funding for their data science and data management projects from senior leaders and investors in their enterprises. We introduce his powerful approach on storytelling, including Scott's technique of bringing vocabulary, voice, and vision as a prelude to successful data management and data science real applications.

The legendary "Data Whisperer", Scott Taylor, joins the Monday Morning Data Chat to discuss master data - what it is, and why you should care. Scott pulls no punches, and this is a fun and candid conversation. Streamed live on LinkedIn and YouTube #data #masterdata #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

Scott Taylor, The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” As Principal Consultant for MetaMeta Consulting, he helps Enterprises and Tech Brands tell their data story. His book – TELLING YOUR DATA STORY: Data Storytelling for Data Management is available now.An avid business evangelist and original thinker, he continually shares his passion for the value of data through industry events, public speaking opportunities, blogs, videos, whitepapers, podcasts, cartoons, puppets shows and all forms of thought leadership.He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble.

When Jen Stirrup speaks, she speaks softly.  The meaning of her words, however, speak loudly!  Jen is CEO of Data Relish, a UK-based consultancy that delivers real business value through solving all manner of business challenges.  You don't earn the nickname the Data Whisperer without knowing a great deal about Business Intelligence and AI.  Jen certainly knows not only those topics, she knows SO much more! References in this episode: Data Kind The Art Of War Blade Runner Tears Scene Episode Timeline: 4:30 - The human element of data, Bias in data, implications of Artificial Intelligence and Machine Learning, and COVID data 27:00 - The BI goal is Business Improvement, escalation and taking principled stands, Data-Driven vs Data Inspired 46:00 - Seeing the hidden costs of some business strategies, the value of even small successes, Diversity and Inclusion, and online bullying 1:29:30 - Jen's mugging story (!) Episode Transcript: Rob Collie (00:00:00): Hello friends. Today's guest is Jen Stirrup. Jen and I have had one of those long-running internet friendships that are so common these days, especially in the data world and in certain communities. But we've also had the opportunity to meet in person several times at those things that we used to do called "in-person physical conferences." She's an incredibly well-seasoned veteran of the data world, but if you're expecting us to be talking about things like star schema and DAX Optimization, that's not really what we talked about. You know that our tagline here is "data with the human element," and we definitely leaned into that human element in today's show. Now, we do talk about some of the important human dynamics about data projects. For example, how the business intelligence industry kind of lost its way in the past and forgot that it's all about improvement and how we're as an industry waking back up to that today. Rob Collie (00:00:54): We also talked about the value of having even one signature success in a large organization that other people can look at to become inspired. And she has some very interesting and well-founded semantic opinions about terms like "data-driven" and why maybe, "data-inspired" is better. Similarly, she prefers the term "data fluent" to "data literate", and she explains why. But we also touched repeatedly on the themes of ethics and inclusivity in the world of data. Now, I have a personal idea that I haven't really shared on this show before that I call "radical moderation." It's the idea that you can be polite, you can be reasonable, while at the same time advocating for sharp change. Now, this is personally what I would like to see emerge in our political sphere, for instance, a form of polite radicalism. We need to change, but we need to be nice. Rob Collie (00:01:52): There aren't many readily available examples that I could point to if I wanted to show you "this is what radical moderation looks like." But now if someone asked me for that, I can point them to this conversation we have with Jen. She is soft-spoken, she is polite, she is open-minded, including the open-mindedness that she might not always be correct. And yet, underneath all of that, is a very firm conviction that we need to be better. And I think that's the best introduction I can give this because I don't want to spoil anything upfront. So, let's get into it. Announcer (00:02:28): Ladies and gentleman, may I have your attention please? Announcer (00:02:32): This is the Raw Data By P3 Adaptive Podcast, with your host, Rob Collie, and your co-host, Thomas you know. Find out what the experts at P3 Adaptive can do for your business. Just go to p3adaptive.com. Raw Data By P3 Adaptive is data...with the human element. Rob Collie (00:02:56): Welcome to the show, Jen Stirrup. It is such a pleasure to see you again, virtually, talk to you. I'm really glad we were able to do this So, thrilled to have you here. Jen Stirrup (00:03:06): Thank you so much for having me. I'm glad we made it work in the end. Diaries, schedules, everything else, but I'm really glad to be here and it's great to speak to you. Rob Collie (00:03:15): I know bits and pieces of the Jen Stirrup story and I know bits and pieces of what you're up to. How do you describe yourself on your LinkedIn profile? Jen Stirrup (00:03:23): So I would describe myself as really trying to help people make their data better. I've just finished a post- COVID data strategy for a healthcare organization in the US and in the UK. The reason I'm doing that is to try and have a big impact. I believe in that, I think COVID has brought around a real stress and a lot of technical architectures, and a lot of data architectures as well, and there're all sorts of pressures. So I've just finished that, which has been a nice piece of work. I've been working with a religious organization on their data as well. A lot of people are accessing their services as part of a recovery from COVID. I think it's been a very difficult, challenging time for a lot of people in terms of mental health, and I like to think that by solving these problems you're actually helping people, in a way to contact, some of whom you may never meet, but that's okay. That's really what I like to do, I think, it's a way of connecting, I think. Rob Collie (00:04:22): We subtitled the show 'Data With The Human Element,' you think of the data field is like this cold, analytical, sanitary, and it's not, right? If you're doing it right, you're having an impact in the human plane, and it's a leveraged impact because you can really sort of touch a lot of people's lives via the central hub that is data. And you've got to keep the human beings in mind, even to be successful at the quote-on-quote "cold, calculating data stuff." If you don't keep the humans sort of first and foremost in your mind, you're not going to design, for example, a good data strategy, like what you just finished. Jen Stirrup (00:05:02): That's right. So I believe that the information ladder is quite important. So we start off with data, then we need to turn that into information, but then we need to turn it into knowledge and then wisdom. And I think COVID has taught us many things. I think it's maybe taught us a sense of purpose, it's something that can help drive all of us. Data can be part of that and I think that data in some ways has been replacing some of the bigger-purpose questions that perhaps we should ask ourselves more often as human beings. With artificial intelligence, particularly, I'm finding that people are replacing data with, perhaps, information, knowledge, or wisdom and say "what does the data see?" and that's fine, but we have to have the context to the data as well. Jen Stirrup (00:05:47): I think in some ways with artificial intelligence, what people are trying to do is build a little box of data and it's becoming this oracle that people are going to touch and say: "So, what does the data say?" It's like we are taking this box and we're trying to turn into some sort of God that we can touch, and it's going to give us all the answers, but if we're going to do that, it has to be a God that we are comfortable to live with, and it's one that we can choose, and one that fits in with people's ethics and their sense of purpose. So, I see data as part of fitting something that can make us all better in so many different ways, whether that is healing or bringing people together. Jen Stirrup (00:06:29): So I think if we could solve these problems where people are feeling that they are not interconnected, then we could start to try and look at that and perhaps think about making people feel whole and feel more together. Because I think what COVID has done is really helped us to focus a lot on data but perhaps not about how we could do things better. It seems that we have an opportunity to decide what goes back in to make the new normal or the next normal. And I'm worried I suppose that I don't see that happening as much as I would like. So yeah, data is important. Absolutely. We wouldn't be here without it and the fact people are struggling with it does pay my mortgage. I still would like us to ask ourselves the bigger questions as well as something that's important to me. Rob Collie (00:07:14): Let me check here. Oh yeah yup, it pays my mortgage as well. We're here for a reason that's for sure. I loved you talking about the AI, this box, that we're going to sort of elevate to the status of a God or that's how a lot of people are viewing it subconsciously. Of course, it's a box that we built. Jen Stirrup (00:07:33): Yeah. Rob Collie (00:07:33): We fed it with our context. It got fed with our assumptions and also our blind spots and now if it makes decisions, that thing starts making judgments and decisions that impact people's lives. It's a tricky proposition, it's one that's best approached very carefully. Jen Stirrup (00:07:55): I agree and I think that's why the bigger questions are important. So say for example, you may have seen the Netflix information series. It was called 'The Social Hack' or something like that. I've forgotten the name, but it was talking about the role of bias in data. One of the researchers found that their facial recognition algorithm didn't recognize a face. And the reason for that was that she's black and for me, I just thought, that's such a preventable issue and how much time do you spend looking at preventable issues? And perhaps not very much. I still see the magpie problem a lot in technology. Companies are happier buying a new technology that they see that's going to solve all their problems, but actually it's not doing that. It's maybe replacing as a bad answer to a different question. We can't see that right now in artificial intelligence. Jen Stirrup (00:08:48): There's some research going on, which will decrease the size of data sets that AI needs in order to create its algorithms and that sounds fine. It's a good piece of research, but what I'd like to see is more researches on collating datasets which are less biased, so that we can think about focusing and trying to make the algorithms fewer rather than focusing on making them smaller. Jen Stirrup (00:09:13): I know a few years ago, you probably remember, everyone talked about big data. Big data was the thing but we didn't ask ourselves if this was the right data. It might be big, but if it's missing out large sections of the population, then that's building an inequality before we get started. I think, even if you don't have the answers, asking these questions is a good thing. I don't have all the answers. There's people working in this field much much smarter than me and they all live and breathe this stuff and I read it, the things that they're doing and talking about, and I think this is such an important part of what we do every day. I think it's really important. I don't know what you think, but there's so much going on in the world of data at the moment that it feels hard to keep up sometimes. Thomas Larock (00:09:58): So first I want you both to remember in case you've forgotten, but you can purchase the Azure Data Box, that does exist. Rob Collie (00:10:07): We will just call it God in a box. Thomas Larock (00:10:09): Azure Data Box, it's actually for shipping storage to an Azure data center, but that's what they chose to call it and I said: "You put your data in the box or it gets the hose again." Right? So- Rob Collie (00:10:20): No no, Tom, it's one: "Put your data in the box." Thomas Larock (00:10:26): So, I mean, that does exist. The first point I wanted to make that you danced around, like Rob you were talking about how we're building this thing and it comes with all of our failings. And I know Jen, she leads discussions on diversity, inclusion, equality and I try to emphasize why that's so much more important and especially seeing the rise and I saw the Netflix special as well, and the Data Justice League. The idea is we need to have those programs in order to have better models. We have to be aware of the bias inherent in the stuff that has already been built. And I think there's a lot more awareness over the last 18 months regarding the products that are on the market that are already failing us because they were built with these biases. And that's a difficult thing to overcome now that you have police departments or governments deploying this technology, thinking, as Jen said, it's this God that is just going to give you all the answers. Thomas Larock (00:11:35): Jen, you also hinted on the thing about the question. So, you're replacing one problem with another, and that made me think of how vital it is that you understand the question you need answered and a lot of times that gets kind of shifted, it's fluid almost. It's like: "Oh, well we were doing this thing we think this next thing we'll solve for it." But the next thing you're getting is actually answering a completely different question than what you thought you were doing and it leads to a huge, huge disconnect. And I think the last thing I would say Jen, I've seen that research about the data sets. I'm encouraged by the idea that we could get people to understand that it's not the volume of data that makes a better model. It's the data that was chosen to be collected in the manner in which it's collected. Thomas Larock (00:12:30): So I know the research on building these models and they're saying: "Yeah, you don't need a billion rows. The accuracy tails off at some point after, say, a million rows." At some point more data doesn't make this model any more accurate but the inherent problem is how was it collected? What were the biases and how was it collected? What was missing? Was it missing at random? Was it missing not at random? The analysis necessary to conduct that research, I think is where we are sorely lacking in business. I know it exists in academia, but those people, they don't scale. There's only so many of those, and there's a lot more businesses trying to get the job done so I think that's fairly important. Jen Stirrup (00:13:13): There is a huge gap between academia and business. I guess there always has been, I do speak to academic institutions from time to time and it's clear that they are doing so much work. They really are, but how that is getting out? I am not sure. Maybe that's why they asked me to come and talk to them so I can talk to other people about what they're doing and I don't mind doing that. I think there needs to be more of that, because I think these scientists, these academics are working in this, have to get access to each other as well and the multidisciplinary aspect of it is really interesting. I did a Postgraduate in Cognitive Science about 20 years ago, and suddenly it's back round again, and it's about philosophy, linguistics, psychology, AI. And why did that go away? Jen Stirrup (00:14:03): It should never have really gone away. I think we got as an industry perhaps Goldstone and such technologies which these things were re-badged as, and we got derailed by the marketing efforts. But I think that there's real room for doing these things in a better way. I don't know if you see this, but I see, or maybe it's my age now, I've been around in the industry for a long time, but I see that people are doing and making mistakes that I first saw 20 years ago, data collection, which you rarely mentioned, Tom, that's been there for a long time and then it seemed to go away. Jen Stirrup (00:14:36): I think that's why academia does help because it gives us maybe more of that consistent backgrounds than perhaps we get from marketing noise, which was goes round in cycles and trends as people are under pressure to purchase these licenses or whatever it happens to be. I wish I had better answers for all of this, I think sometimes it's about just asking these questions, blogging, talking about them, putting them on social media so that when people are thinking, "what do I do about data strategy?" That these things are part of this. I saw a study recently saying that companies are decreasingly likely to include ethics and these questions and bigger societal questions as part of the data strategies as you're trying to get the link. But it disheartens me because I thought I could see that the voices are getting squeezed out. Rob Collie (00:15:25): Decreasingly likely, like we're trending- Jen Stirrup (00:15:28): Trending down. Rob Collie (00:15:28): You know, it'd be one thing to be flat, right? I mean that would also be disheartening, but to be decreasing, decreasingly likely to be factoring in ethics into a data strategy. Now we've been talking a lot and I think it's a good thing to continue to talk about the implications of AI and machine learning in this space, the business intelligence industry isn't particularly fraught with this kind of problem, right. Transactions happened, or they didn't, you know, and it was the number of six or a seven. I mean like, you can get it wrong, you can have bugs, right. But there isn't any like objective debate about what, there shouldn't be any way about what actually has happened. But the decider systems, are a completely different game, like where should we route this patient? This is going to have a huge impact on their life. Rob Collie (00:16:21): That's a very, very, very different game and we've been talking about sort of like, the completeness of the data that is used to train these systems, but I think it's really instructive just to stop for a moment and go, you know what, even if we were able to feed these systems a 100% comprehensive picture of today's world, we still have to accept the fact that we're telling it that today's world is what we want. Right. And maybe we don't, you know and there's always a judgment in training these systems, we tell it what is a success and what isn't a success. Our unintentional biases can leak into this stuff in a million different places, even if you suddenly had God-like comprehensive powers to feed it, quote-on-quote, all the data, right. It's still leaky. It's still fraught. Jen Stirrup (00:17:13): Yeah and actually, I think it's an extension of their problem that we see just when we're building a data warehouse. Sometimes I'll go into a customer and they'll say, "you know, we want to see our data and see our latest vendor here," and then I'll say, "well, is it preserving the data or is it just, you know, been reamed out the other end, what you're doing with it? Where you're storing it?" And then the argument against the data warehouse as well. It's not going to capture everything in the possible universe of possibilities in my business, so I don't want to do it. And I find the argument goes something like, "there's an edge case that it won't cover." Others, "this edge case, it won't cover here." And then you have to say, "well, you know okay. So it's not going to cover all the possible edge cases, but it will cover 80% of what you need, and the rest, can go to shadow IT or shadow data systems or wherever they happen to be." Jen Stirrup (00:18:03): And I think we're still trying as it's a bigger picture perhaps trying to control everything that happens around our business, but we have to be flexible enough to cater for these scenarios. We haven't seen this before. I think that's what makes the AI so difficult actually, as we have more than one type of AI, we have a general artificial intelligence, which is more like Terminator, you know, these kinds of things. Rob Collie (00:18:29): Innocuous stuff like that. Thomas Larock (00:18:30): Harmless. What's the worst that could happen. Rob Collie (00:18:32): Yeah. I mean. Jen Stirrup (00:18:35): Well, I think as humans, we do enough damage to ourselves, most of the time we don't need a Skynet. Thomas Larock (00:18:38): That's true. I agree. That's often my reaction to, well you know, like self-driving cars, like what if it makes this mistake? Okay yeah but the human being track record behind the wheel, we're not trying to be perfect, we're just trying to be better than people, which is a little bit more achievable perhaps. Jen Stirrup (00:18:56): Exactly and it's all a bit context, which is how to program. You probably remember a few years ago, at SQLBits say Tom, Steve Wozniak visited. I don't know if you were there for that SQLBits but Steve Wozniak is one of the team that founded apple. You must know who he is, but he's talked to us about the Wozniak test for AI, the testers will have an artificial intelligence sought of robot come into your house and make you a coffee from scratch. Now that involves a lot of contextual knowledge. They have to find your kitchen, they have to get your ingredients and get a cup, you know all that kind of thing and that requires context. And that's more general AI, that's more difficult to program. But if we're to think with CEI being more successful for businesses automation productivity, and it's just trying to do something, one thing really, really well, something that will help a human to make better decisions faster. Jen Stirrup (00:19:51): Such as perhaps parceling out x-rays, which don't show any presence of a tumor as an example, but we then get the 10% of x-rays that makes sure something and passing those onto a human to look at. So there's plenty of rooms for defining what success looks like for us for artificial intelligence I think. With business intelligence, your right, we should have one version of the truth. People are still living so much in Excel and Google sheets and things of empires away, and that are sitting in their laptop. How do you move that to the cloud? So you move them perhaps to office 365 or a Google work space, and then you're trying to encourage people to rethink the processes about, Hey why do we save stuff in the cloud? Or why do we make our decision making more apparent? And it seems a bit difficult to ask AI to make its decision-making more apparent, when actually a lot of people spend time hiding or umpiring the knowledge anyway. Jen Stirrup (00:20:49): I don't know if you think this, but I often think business intelligence problems are change management problems in disguise. It just happens to be showing up in the data that there's a problem. Thomas Larock (00:20:59): Yeah. Rob Collie (00:20:59): Ultimately it's not about knowing, it's about improving. Knowing that there's a problem and even knowing what's causing it is really just the beginning. Very often it's like okay, now what? This is going to be a really difficult problem to address operationally. Jen Stirrup (00:21:16): I think we forget the process of optimization and business intelligence. And I wonder if that's the reason why AI is becoming so prevalent at the moment, because it is much more clearly talking about optimizing and improving processes and automating. I think in business intelligence, we have almost stopped talking about optimizing business processes. I don't see it quite as much, I wonder if we get sort of caught up in data visualization, you know Tableau came along and then power BI and everyone started chasing after that. We're perhaps forgetting that actually we're doing all that for a purpose, which is to make something better somewhere. I don't know if you find this but, I obviously run [inaudible 00:21:54] business and it's very hard to get customers to agree to a case study because they don't want to show that actually they were in a bad place and they don't want to show the competitors that they were in a bad place. Everyone's ashamed of the data. So it's really tough. Rob Collie (00:22:07): I've seen sort of multiple facets of that. So first of all, yes, everyone thinks that they are uniquely broken, everyone's organization that they feel a level of sort of like discomfort and shame about where they're at today or where they were yesterday. They feel like they're the only ones, but we see so many organizations per year, especially the kinds of projects and the pace at which we move the world is very much uniformly broken. No one's really behind, everyone's way behind of where you'd sort of like as a dispassionate observer, you'd expect people to be a lot further ahead than they are, but no, no, really the basics are still not sorted out universally. We're still kind of in a dark age, in a way. Jen Stirrup (00:22:51): Yeah. Something, I see really basic issues of one customer example of talking about where they were calculating the mean incorrectly for two years. And then two years before that, for another two years, they were calculating the median incorrectly in Excel. What they were doing was it were taking the middle value of a column. So of course, if you sorted the column next to it, the value changed. And they said that that was the median. And I said, "okay, so you've got a column of 20 items. Are you telling me that whatever's a number 10 is the mean?" And they said, "well, yes, that's in column B." What happens if you change the order in column E from perhaps alphabetical order to reverse alphabet order, the values can be changed, right? And they looked at me and I said, "why did you calculate it like that?" Jen Stirrup (00:23:41): And they said, cause we can calculate the mean using Excel formula. So eventually I said, "why are you using the mean," because it's quite sensitive to outliers the median's better. and then they said, "well we've tried that but we couldn't calculate the median either." I said, so okay "for four years you've been trying to calculate the mean and the median incorrectly in this one spreadsheet. Can you tell me about the rest of your spreadsheets? How often are you trying to use the median or the mean all of it incorrectly?" And I think it's probably the only time in my 20 plus year career, I've seen a customer actually punch himself in the face and it was just absolutely stunning. And he said, "I'll go and speak to the statisticians." And I thought, you've got statisticians working here. I'd love to meet them. Jen Stirrup (00:24:26): I wonder what they're telling you. And that was my second deal in sight, I was on the on and off for six months. And that was just the first problem I found. So I know we talked about data literacy. I'm not a fan of that phrase. I prefer fluency or something along those lines. So I don't want to assume people are data illiterate. Because I don't think that they are, I think we're born naturally within us an innate sense of numbers in a way, we can tell more from less, right? My dog can do it, right. So if I got five treats in my hand, he knows I've got others. If I just give them one, he's not stupid, he has a sense of quantity. And I think it's about, we need to get better in industry, perhaps explaining results, findings, conclusions, and context to people instead of just throwing dashboards at people and expecting them to understand it. Jen Stirrup (00:25:16): If somebody recently sent me a scientific article which was all about COVID and some testing that they did in mice, and I could read it, but I couldn't understand it because I don't have a background in medicine. I read the abstracts and I read the last paragraph and the first paragraph, but I didn't read the rest of it because I thought this is way beyond me. I don't understand what they're trying to say. But I think for me that highlighted a problem with data literacy, I could read it, I couldn't understand it, and I certainly couldn't act on it. And I don't want to give other people who are trying to consume business intelligence products in some way, whether they're dashboards or even dumps from Excel, that they just don't understand what they're getting. How we do that, I think is perhaps focusing in data translation. Jen Stirrup (00:26:03): How we do that, I think, is perhaps focusing in data translation. I had a woman who worked for me, she actually was a qualified librarian. So, her insights about information retrieval were very interesting. I learned a lot from her, because that was a little bit the data. And she would say things like, "Jennifer, Google is not the only search facility in the world. We can use so much more," because she's accessed all their library systems around the world. And there's so much information we don't access because we can't, usually. But the point being that what I learned from her was about translating things, where they were easier to understand for other people. And I think it's an incredibly valuable lesson, and the world needs more librarians. Rob Collie (00:26:43): There's a lot here, right? Business intelligence was always a means to an end, but because it was so difficult, it was just so incredibly difficult to even get a halfway-competent system instilled, built, configured. When something is that hard for that long, it becomes its own goal after a while. It's easy to habituate to the idea that this is the goal, intelligence is the goal, knowledge is the goal. No, no, no. Improvement was always the goal. What's really been fascinating for us is, when we see our clients, the people we work with, when we see them start to get the BI problem under control for the first time ever, their gaze immediately sort of zooms back and they start thinking completely unbidden by us. We don't have to seed this conversation. It just happens. They start looking at the bigger picture now and going, "Oh, okay. So, now this information needs to feed into better decision loops and optimization and things like that. And how do we facilitate that?" Rob Collie (00:27:53): And from the beginning, we try to counsel everything being built around that "taking action" thing. You can build an incredibly informative dashboard that is intelligent, it's a work of art in many ways, on many levels, and it can be useless. It can be factual, it can be impressive, and it can be useless because you can't use it to make any improved decisions. I've been guilty of this. I have built things like this, like, "Ta-da." And the client doesn't even have the language to push back. Jen Stirrup (00:28:30): It's something I've tried to keep in mind now is the utility of what I'm actually doing, because people just want data for the sake of data, and they get that. I think, sometimes, they don't know what to ask for, so they take something because it's better than nothing. And they'll say things like, "Right, I want the last five years of data and 191 columns, I want it all on the same page, and I want to be able to print it." And then you have to say, "Well, let's think about how feasible that is. You'll get five years of data, it's not going to fit in one page. 191 columns is going to be really small. So, let's have a..." People ask that because they don't know what they want. Jen Stirrup (00:29:06): About a dashboard recently, a health and safety dashboard, it was using power apps as well. So, the company, if they saw a health and safety priority issue, they could use the app, if they were health and safety professionals, and the app would record data, you could upload a photograph, and then that would go into a system which you could then see in Power BI. And the nice thing about that was you could see improvements over time because people could get their health and safety issues resolved more quickly, so things like boxes stacked against fire exits, slip and trip hazards. Jen Stirrup (00:29:43): Now, it may not seem very interesting, but actually, the reason that project had happened was because someone that had been in a health and safety incident and it had not been tracked properly, and the idea being that they were trying to improve the process. But sometimes, I think data problems and data solutions happen because of two things. One is you need an executive sponsor, and the second thing is a crisis. And together, the executive sponsor and the crisis will engender change somewhere. And that change management process so often turns into a business intelligence solution. And nothing is an industry. It's something I'm personally trying to always keep in mind is: what's the purpose? What's the optimization? What problem am I trying to solve? Rob Collie (00:30:30): Yeah, one time, I was asked by a client to help debug a report that was really slow. So, this is great because this is an example of a report that I didn't build, right? I can use an example that wasn't one of my own families, but I'll tell my own as well if you want. But I go, "Okay, I'll take a look at it." I'm expecting some sort of DAX or data modeling problem or something like that. And they show me the report, and it is a 100,000-row pivot table. The pivot table has a 100,000 rows in it. There's DAX behind it. It's a DAX data model behind the scenes, but the report itself, the output is 100,000 rows. And before I even engage, I just turn and look at them and say, "Oh, my God, who was using this? You don't have a performance problem. It's..." And they're very insistent. "No, no, no, no, no. This is the thing. We need this." I'm like, "All right." Rob Collie (00:31:21): So, I start looking at it, and it's crazy how many columns there are. And it was a list of every employee and every location that they have in the country, which was hundreds of locations and thousands of employees. And for each employee, their scheduled time-in and their scheduled time-out, and their actual time clocked in and actual time clocked out. I turned back at him again and I go, "Okay, really? What are we doing here?" And they're like, "Okay. So, we have all these regional managers that are looking at this multiple times a day, probably eight times a day or more, to try to figure out if any of their stores are empty, aren't staffed because people didn't show up." And I just smacked my forehead and I go, "You don't need the timecard report," which is what they called this thing, the timecard report, "You need the empty store detector." Rob Collie (00:32:18): And I mean, there was no way to make this thing faster. I mean, this thing was such a gross misuse of technology. I just went to the whiteboard and I sketched what the empty store detector could look like, and they're like, "Oh, that's great. We'll never get our managers to switch over to using it, so let's just go back to fixing this other piece of junk." Jen Stirrup (00:32:37): Yeah, because something that I struggle with, personally, is the idea of surveyance reports. It's something that really bothers me. I've pushed back on a few customers to see, "Are you micromanaging or are you surveying? What is it you're trying to do?" On occasions, I have escalated it to say, "Look, this report is probably been used to hit people for the head, and I'm not comfortable with this because I think this has gone beyond micromanaging." And we had set the scope of the project of the thing we were supposed to deliver. So, I'm going to escalate this because I want to understand better the purpose. And if I'm wrong, we will deliver it." Jen Stirrup (00:33:12): And normally, when I go back and see that, even in that particular instance, I showed the senior management and I said, "Your middle management want to do this." And they said, "No. We are not spending time doing that. We need to understand the wider context. If there is any issues going on with staffing, then this is probably a symptom rather than the cause of the issues, if people are being watched like that." So, I think some teams escalating, as much as I don't like to do it, sometimes is the best way forward. Rob Collie (00:33:44): It takes a lot of professional courage to do something like that. For example, have you ever taken one of those principled stands and ended up no longer working for that client because they basically fire you for not staying in your lane? That's a risk, right? Jen Stirrup (00:34:01): Yeah. It is. I've never been fired for that, but I have said, "Uncomfortable, and I'm we going to stop delivering services, and we need to decide on an exit strategy." There's different ways you can do that, right? So, you deal with the current project. You then say that you're busy for the next century when we come back to you for other work. I don't like doing that because I often feel like you should give them an alternative to say, "Well, here. I can't deliver it, but I know someone who can." And then I recommend one to my network. But the thing is, when I make these quite principal stands, people back down often, or they back down and they just asked me to do it. But when I've gone back to people like that customer, who come back to me for extra work, I've done some investigating work and I've found that they have not implemented a thing that I've been worried about or concerned about. Jen Stirrup (00:34:49): So, I think, sometimes, if you do speak up, people are maybe surprised by it. It's maybe different who it comes from. And I think, perhaps, even a soft Scottish accent, smiling sweetly at them and saying, "Can you explain to me a bit more about the reasoning behind this? Because your team want to do this thing, but I have some discomfort because it's outside scope." And they're not telling them, and they're very direct. Wait at first, but they start to get their message. Jen Stirrup (00:35:16): A former boss of mine years ago, he said I had a soft rein approach. I actually think that's a nice way of putting it, where, as much as I might be tempted to go in all guns blazing, I'm trying to gently bring it up and then bring it up again a bit more firmly, and then, suddenly, people are starting to understand better. But that's me having to probably, sometimes, exert a huge amount of self-control as well. But I think that's part of the consulting game. It's very tough. But I think seeing something like that happen, I think the reason it happens is because people aren't thinking about it longer-term. And me as a consultant, it's easier, perhaps, for me to think about it long-term and also a bit more closely as well, because you are thinking about the consequences of what you're trying to do, the purpose. Rob Collie (00:36:04): Yeah. If you're good at data and you're experience with it, you spend a lot of time with it, that allows you to put some of those things a little further down in the subconscious, and the rest of your human faculties can resume working, whereas, I think, for people who data is still this arcane thing, it's not the thing that they've spent their lives with, it's just really easy to get target-fixated on the data, data, data, data, right? "It's not about the people, we're trying to figure out the data," right? "And inform me," and all of that. Rob Collie (00:36:33): And I think it's like when you're first learning to drive, I couldn't have the radio on. The radio was really distracting. And you certainly couldn't have a conversation with someone next to you. So, all you can do just to make sure that you're turning the wheel the right amount and all this kind of stuff. It's just overwhelming. But once you internalize all that stuff and you build the muscle memory and all those sorts of things, now your brain is free to do some other things. Like this data fluency thing we were talking about, it's neat how, as you climb that slope, you're never there, it's a perpetual journey, the other parts of the equation like the human things, right? They can come back. Rob Collie (00:37:12): An example, even just from our own business, we do a lot of internet advertising. And sometimes, when people at our company are thinking about this, now the wrong way to do it is to go and like, "Oh, let's go look at the ad words API and let's get fascinated by the tech around this." And I'm always trying to remind people that, no, no, no, we're trying to scale a human interaction. That's what we're trying to do. We're trying to reach people with our humanity- Jen Stirrup (00:37:43): I think that's so true. Rob Collie (00:37:43): ... and we're using a technological system to do that. It's a tool for the other thing. Jen Stirrup (00:37:50): You're so right. I think we should be using technology empower and enable. And I think my personal mission is about helping people. I find that rewarding, personally. I like things with a purpose, so that's why I do charity work with organizations like DataKind, because when you get someone crying because you've solved a problem for them and you've helped them, you know how incredibly grateful they are. But I think, for me, that's why diversity and inclusion, equality, and intersectionality more recently has become really important to me. Jen Stirrup (00:38:21): I'll just give you a few examples that's in my head. I did a project recently, and there was a woman of color in my team, and I felt that she was being talked over. I'm used to being talk over, softly spoken. But I could see it with her. And I just made a conscious effort to say, "I'm sorry, but I don't think she's had the opportunity to speak, and I can see she's tried to have some input." So, some of it's a bit like that. But some of it is directly saying, "What do you think? Sorry, we haven't heard from you," and pulling people out. And you know what? She was and is still incredibly insightful. And sometimes, the best data scientists I work with are people who can't code. And I think about her and I think about another woman of color as well that I work beside. Jen Stirrup (00:39:06): Fantastic data scientists, they both know Excel, but they can't write a line of code. And the reason they're so good is because they are such fantastic questions. That means the rest of us who can code have to then go and get the answers. And I think the knack of asking the right questions is such a gift, it's such a skill, and it's something that I am consciously trying to improve myself on. And I think diversity, inclusion, and equality is really important, but we wouldn't get anywhere with any of that if we're not allowing people space either to talk or we're not able to give them the space to ask the right questions. Jen Stirrup (00:39:42): Now, I am constantly learning every day. And to do that, I'm having to learn to get better at asking questions. And it is a skill to ask, but I think, when we're dealing with data, it's about helping people not to feel stupid if they're asking questions, because I think, with these particular cases, it's very easy to feel diminished in a conversation where other people are understand the technology, they can code, you can't, but you've got an insight. I know we talk about data-driven, but I like the term "insights-inspired," and I wish we had more of that because that, I think, gives us room for other people who perhaps don't understand the technology but do have business insights that I would never get, because they help me interpret the code or the data to make it better. Thomas Larock (00:40:28): So, you said data-driven, but you prefer insights-inspired. I think those are still two different things because, when I think of data-driven, I actually think of that in terms of, "I'm going to make a decision based upon what the data's telling me, not upon my feelings." The insights-inspired, to me, is how I get to the question I want answered, right? But I'm still data-driven. I think there's some overlap, but I also think there's a lot of space there where they are distinct, because I do believe in data-driven because I've been in those meetings where somebody's like, "Yeah, I don't really care. We're going to do what I think is right." "But the data says something completely opposite." "Yeah. That doesn't matter to me." And lots of those cultures exist. I love insights-inspired, and I'm going to steal that. Jen Stirrup (00:41:16): That's fine. I think we need both, actually. I'm sorry if I wasn't clear. But you're right, there is a good impetus for people to think, "What does the data say?" And I like that. I think the "insights-inspired" piece will help us to understand if the data's right. And I'll give you an example of something that I did. So, I was doing some work for the national health service and there's some data missing for a hospital, and it was not an insignificant amount of data. It was for about five years, the data. And I searched for it all morning, and I was just about to ,arch down the corridor to go and corral a DBA to ask him, Have we lost any data? Because I cannot find this." Jen Stirrup (00:41:55): And then, when [inaudible 00:41:56] was passing, she said, "How are you doing?" I said, "Oh, have you ever worked at this hospital?" I won't mention which one it is. And she said, "Oh, I was there until it closed for five years and it merged with another hospital." And I thought, "Oh, you've just answered my question. Right." Because I was sweating beads because I thought, "We've lost five years' worth of data." And I thought, "We've done that. We are in so much trouble," because it's a lot of data. It's a lot of patient data. No, no, no, no. They went somewhere else. And there was a very good explanation that I would never have got by the data. I could have hugged her. Jen Stirrup (00:42:31): And to this day, I still feel the palpable relief, because I was walking in the hospital, thinking we need a really good explanation for this. But according to the data, it was not there. So, I think, when I look at data-driven, I think they're two sides of the same coin, because insights will tell you what the nurse said, "Well, actually, it's like this," and they will add to the interpretation. Jen Stirrup (00:42:54): I just sat in a meeting once where one of the leaders said, "All right. So, we've got the data now?" I said, "Yes, everything's fine." And in front of four of his team members, he said, "So, we can get rid of the business analysts then, because we've got the data now." And even when I mention this, I still, at this point, feel my blood pressure rising, which is not good for me. I am well over the age of 40. And actually, I was stunned. I said, "How are you going to understand the data if you don't have your business analysts. Who's going to tell you what it means? "Oh." I said, "Are you really thinking that you can just throw your data at a wall, see what sticks, see what's left, and that's going to drive a business? Because, pretty much, that's what you're doing, if you are not involving the people who understand the business." Jen Stirrup (00:43:43): And after the meeting, I mean, some of them were crying, saying, "He was talking about me losing my job." And the people impact was terrible. So, this is where I've got my principals coming in. So, I went and I escalated that afternoon, and he was taken off the project the next day. That was due to happen. That was just outrageous. And if any of you who are listening and this is you, I love that team, their insights were incredible and I learned so much from them. And to the leader in that organization, please listen to your team members. You will get so many many great insights. Rob Collie (00:44:23): Wow. Jen Stirrup (00:44:24): Sorry, this is very cathartic for me. I'm glad you've brought me on today. Rob Collie (00:44:33): I mean, just watching your face as you told that story, I can see the emotions that you're feeling, right? Jen Stirrup (00:44:37): He's going to get this. Rob Collie (00:44:38): And it's a mix, right? It's a mix of the beauty of some of these people that you worked with, right? Contrasting with like this horrible, horrible attitude, at the same time, from this one individual. When you have all those feelings at the same time, it's like you need a new name for it. It's like, "What is this feeling?" Jen Stirrup (00:44:56): And I think the industry is like a pendulum, so we go towards data-driven. And for some organizations, they need good data-driven, so Tom's given a great example. But sometimes, it goes too far and they say, "Yeah, I read that buzzword. I'm going to do that." And then, there's an expense, something has to give. And that, unfortunately, was his team. Like you said earlier, Rob, it's about the people. We should be there to help people by helping people do their jobs better, not necessarily replacing them. That was not ever on the menu. Rob Collie (00:45:29): Yeah. It's counterintuitive. Sometimes, when your data system gets better, the right move is to have more analysts because there's more ROI in having them. Even just hiring a data professional services firm such as yourself, the reason to do it is because the ROI can be massive. Jen Stirrup (00:45:51): Yes. There's lots of unseen costs. I worked with an accountant last year who spent four out of five days a week merging Excel together. And I sat with her, I got to know her pretty well, I mean, remotely because of COVID. And eventually, she said, "Oh, I'm looking for a new job." And I said, "Oh, really?" And she said, "I did not incur a graduate debt to sit and do something that I could have done without my degree." She'd put a lot of effort and, same in the US, lots of student loans to do a degree. And she said, "Technically, my job title is accountant, but I'm not accounting. I am munging data around in Excel." And one of the projects I had recommended was data integration, right? And they wouldn't go forward it. They kept saying, "No, no, no. We've always done it this way. So-and-so om accounts does all that." But they never asked her what she wanted. Jen Stirrup (00:46:43): So, she left, and I was not a bit surprised because she said, "I want to be an accountant. I want to account." And I know that it's not my personal lifestyle. It wouldn't be my choice of a job, but for her, she just loved that, and she wasn't getting to do. So, sometimes, the causes are quite unseen if you're not looking after the processes or the data, because that incurs hiring costs, then, on staff onboarding costs that don't get included often as part of these business strategy projects. When I'm doing a data strategy, I try to include them, to say, "But what happens if you change? But what happens if you don't?" And you're going to lose people because your people, very often, want to be skilled in the later technology. Jen Stirrup (00:47:25): And I'll give you an example. One customer I worked with said to me, "We need your help with reporting services, SQL server." So, "Okay, good. I like reporting services." Then, they talked to me and I said, "What version are you using?" And they said, "2005." And I said, "Why?" "Because the application that's using it requires SQL server 2005 and we can't upgrade." Said, "So, what was the application written in?" "VB6," which you may have heard of that technology. It was around in 1999. It was last century. So, the data state was antique. I had no idea that it was that bad. But then, the application came up, and Microsoft still do a version of a Visual Basic. You can go to the site, the latest version... But the point being that the staff and that place had settled for VB6, they'd settled for 2005. That doesn't mean that you're getting the best team members. And when we worked, it was recommended an architecture. Said it was not touching it with our [inaudible 00:48:30]. Rob Collie (00:48:30): I'm still very fluent in VBA6, so maybe after we finished this show, can you give me the information of this organization? I might go apply. The last place on earth that VBA6 fluency is... Actually, that's not true. It's still being used everywhere. It's just not being used centrally. Jen Stirrup (00:48:53): Yes. I did say to them, "I am not touching any software that was not built in this century. So, if it's in the last century, you've no chance." So, re-architected, actually, we're using the Azure Cosmos... Thomas Larock (00:49:04): It's a good rule. Jen Stirrup (00:49:05): ... and dot... Yeah, it's a good rule. It's a rule to live by, you can quote me on that. I use no software built in the last century. In fact, I'm going to make that my new company advertising strapline. That's great. I like that. So, they're happily in Cosmos and .NET. And we used that because the developer said, "Hey, does that mean we get to modernize?" I said, "Yes. And you will either modernize or I will leave. Your bosses are going to have to modernize." So, they did. But again, that soft Scottish accent comes up. "Well, why don't we use software that's built in this century?" Rob Collie (00:49:42): It's a devastating maneuver. If we were making a card for you in a trading card game, that would be one of your two power moves, right? Soft Scottish accent. And the description of the power is something like, "Removes all defensive screen cards from opponent." Thomas Larock (00:50:07): Disarming. Jen Stirrup (00:50:10): Absolutely. Yeah. It's just funny how the data problems are really throwing up what's wrong with the organization. Obviously, they did that, but two years ago, I went to visit them again, just before COVID last year. They'd implemented a data science team and they just wanted some strategic consulting. And I was really pleased with how they turned around. So, sometimes, if you just find a problem like that, a small success, building those small successes, and they were allowed to up. I don't know if you see this, but big thing of what I'm doing when I'm in organizations is change management, but also a lot of that's people. And people tend to align themselves with success. So, if you can just show one small success, people get on board with it. Rob Collie (00:50:53): Yeah. I mean, it's everywhere in humanity, right? We're fundamentally pattern-matchers. And if you haven't given a population any positive patterns to match, no examples, it's amazing how stuck you can be. But one success, right? We have an infinite percentage increase in our population of successful examples. We went from zero to one. Like you say, the dog knows that there's five treats in your hand, right? We're not dumb. If there can be one success, there can be more. But if there's zero successes, that's powerful. Jen Stirrup (00:51:25): Yeah. And I don't know if you see this problem, but it's something I see a lot is people think maybe Tableau or Power BI, they buy this, it's going to give them a success. And it does, until the data starts to get hard. And then they either have to scale up in DAX, which is fine, but sometimes they don't have room or bandwidth to do that, so they get almost a bit depleted because they realize, actually, data's hard. We've never really nailed data as the human race. Rob Collie (00:51:55): It's always hard. Unfortunately, to sell software, to a certain extent, you have to sell the lie. If you're a software vendor, you have to se... Rob Collie (00:52:03): ... have to sell the lie. If you're a software vendor, you have to sell the lie that this tool is the magic fix, that it's going to make data easy. And I do actually, in a weird way, I kind of like blame Tableau for making this worse, but while at the same time, being very grateful to Tableau that they made interactivity a must have. Jen Stirrup (00:52:24): Yes. Rob Collie (00:52:24): I think they were actually, more than any one entity, responsible for us breaking this notion that reporting services and similar tools were it. Jen Stirrup (00:52:34): Yes. I remember the first time I saw Tableau. I had been hired as a developer for SQL server [inaudible 00:52:40] services and my boss said, "I think this is a future, this stuff, Tableau. Here's the download link. Tell me what you think". 10 minutes I was completely hooked and it changed my career because otherwise I would have probably stayed in the database reporting world and I suddenly thought there's a whole world here with stuff. So I love what they did. I really, really think it was groundbreaking. Thomas Larock (00:53:01): At what point did a report just become synonymous with the word "Tableau"? I have a limited experience and maybe it's an outlier, but to me, I always hear people say, "I'm going to run a Tableau report". I mean, it's just a report. I worked with Crystal and BusinessObjects, same thing I guess. And do people always qualify the type of report they're running as if that makes it more special or do people always say, "I'm going to run a power BI report"? Why is it always a qualifier? And in my case, I always hear, "I'm going to go run the Tableau report". I'm like, "It's just a report. It doesn't really matter what's the software that's doing it. It's just data. It's just a report". But I hear that a lot. I just figured I'd ask you two if that's the same experience? Jen Stirrup (00:53:43): Yeah. I think I'm hearing that more and more and I actually think it's almost going the other way, where people are only wanting interactivity, they're only wanting things they can click and tick. And what they're not wanting as much is a SQL server, mahogany red, forest green, slate gray, corporate template, because that was the what, about four templates you got with reporting services. So I see that more and more apart from the finance world. They still very much want it. But what I'd still see is a big need for tables. People still want to export to Excel. And I think it was you, Rob, who actually said this years ago, that the third most common button in Tableau is something like "export to CSV". Thomas Larock (00:54:26): Yeah. Rob Collie (00:54:28): Yeah. The third most common button in any data application is "export to Excel". Thomas Larock (00:54:32): Yeah. Rob Collie (00:54:32): Behind "OK" and "Cancel". That's the joke. And what it is, is an acknowledgement of, again, the human plane that this report, this app, does not meet your needs. It's in a way like if you could instrument your organization and find all of the "export to Excel" buttons that are being worn out, those are like the hotspots for you to go and improve things. That button being, click, click, click, click, click, click, click all day long, is telling you that there's a tremendous opportunity for improvement here, both in terms of time saved, but also quality of result. Quality of question that's even formulated. You mentioned questions earlier, asking good questions. Here's the problem. The ability to execute on answers and the inability to execute on answers, the friction, the inertia, that works its way upstream into the question- forming muscles. The question-forming muscles atrophy to a level where they fit the ability to execute on the questions. And so when you suddenly expand the ability to answer questions, it actually... You've got to go back and re-expand your question-asking muscles to be more aggressive, to be more ambitious. Jen Stirrup (00:55:52): Yes. I think sometimes the data-driven piece is trying to, in a way, subtly bring that back into play. It's okay to admit that we don't have all the answers and it's okay to admit that we need to ask questions. I think there should be more of that. Something that, certainly earlier in my career, asking questions was discouraged. It meant you didn't know it. It meant that you were vulnerable in some way. And I think as an industry, we need to encourage people to ask questions. I think with the diversity inclusion piece, try and make a conscious effort. If I think someone in the meeting is being quiet, regardless of the background, but at least I'm trying to watch out for that now, whereas maybe 20 years ago, I wouldn't have realized it, but sometimes people do sometimes need that extra help to speak up and speak out. They often don't know what to say or how to beckon to a meeting and say something. It's quite difficult. Jen Stirrup (00:56:51): Especially if you were being measured in your performance. I think sometimes people see things very confidently. And actually when you start to pick it apart, you think, "I need to as a person, stop believe in confidence and maybe thinking is that right, not how it's being delivered". I think they're stolen for quiet voices, hopefully like mine, who are trying to say things but I do find that harder to get heard. I think it's good that you do podcasts like this because I think it gives people the opportunity to talk about different ideas and how they impact people because that is important. There's loads of vendor podcasts that will talk all about the technology but we need to know better how to apply it. Rob Collie (00:57:31): When we were talking about starting this show, it was pretty clear we did not need another tech show. People who are working in tech, but are human beings, like yourself, and who are focused on helping other human beings. We weren't sure if it was going to work. It was one of those like, "Are people are going to listen?". Thomas Larock (00:57:45): We're still not sure. Rob Collie (00:57:50): We knew that we were going to like it, but yeah, it's building an audience. I've enjoyed it. And plus, it's an excuse to get together and talk with people such as yourself. If we just pinged you out of the blue and said, "Hey, you want to get on a two hour Zoom call with us and just catch up?". That's going to get pushed and pushed and pushed and pushed, but, "Oh a podcast? Oh, well, yeah. That's exciting". Jen Stirrup (00:58:14): Yeah. I know what you mean. It's good to, I think, to try and translate data and technology into something people feel is within their reach because I think there is still an element of people who are almost being scared of working with data. I deal a lot with CTO's, CIO. I was busy CTO and some way reports sent to their CFO because their CFO is over all of it, keeping costs down. The CTO has to work really hard to justify them. And I think what they want, ultimately, is not to appear stupid or not to know what they're doing. So some of these leadership conversations I have are about people saying, "Explain these terms to me. I don't know what a data lakehouse is. Do I need one? How's it different from a data lake? What about the warehouse? Is that going away or is that rebranded as well?". I know Microsoft talked about data hubs recently. If you're a data vault person, a data hub means something quite specific. It's been a term around for 30 years to mean something else. But I think sometimes people get very confused with the terms. Rob Collie (00:59:16): Like for example, the noun "dashboard" in Power BI, right? It's just a head clutching frustrating mistake. I mean a Power BI report is probably best described as a dashboard. The multi-visual, interactive experience, lowercase D dashboard is what I always want to describe it as, but no, no, no, no. We repurposed that word. Jen Stirrup (00:59:41): I know, and customers don't always understand it because they say, "Well, actually my report looks exactly like the dashboard. So I don't understand this publishing thing". So I have to try and explain that actually, we can take data from [inaudible 00:59:55] here and you can extra things. I'm interested to know actually, how much Power BI users spend actually making dashboards as opposed to making reports. And I just wish we'd ever the answer to that because sometimes you just want to get reports that they can run in their desktop or not always sometimes use a browser and just have the reports and have them open on the actual dashboards higher up. So I feel that's a bit of a separation that maybe wasn't required to have. But Tableau does something similar, doesn't it in a way? But I think with Tableau, it's a bit more clear that you're putting these things together. Rob Collie (01:00:29): Well, we were talking at the beginning about the importance of comprehensive training sets. Well, let me just tell you, we only need one data point here. I, as a Power BI user, have never once created an actual Power BI dashboard. So let's just conclude that that's it. No one uses them. But yeah, I've never felt compelled to need one. I tend to put together, what I need in the report. Jen Stirrup (01:00:56): Yes. And that's what I do because I'm trying to get the customer from A to B. I'm trying to do it quickly and I can see that they've reached on that tool ceiling of where they want to go and then they've got this other thing they need to do and they don't understand why. So sometimes it's a battle I just don't have because I just think, "You know what? These often been through so much to get to that point in the first place, cleaning data and getting access to the data and all the things that are hard and even understanding what they want in the first place". I try and work out where the fatigue is. Rob Collie (01:01:28): Yeah. I think there's a certain hubris just in the idea that a user will go around and then harvest little chunks out of other reports and take them completely out of context. Anyway, we didn't come here for cynicism today but- Jen Stirrup (01:01:43): I have plenty of that. Rob Collie (01:01:43): But it's still there. We can't really help it. So it's come up a few times and I want to make sure we actually make some time to talk about it specifically. So you've mentioned a number of times, inclusion and diversity and already a few anecdotes within your own professional organization, within your own firm. Outside of your own data relish organization, what are you up to in this space around the diversity and inclusion as a cause? You're very active in the community in this regard. Can you summarize for us what all you're up to? Jen Stirrup (01:02:15): Yeah. I've started there to talk more about intersectiona

Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories. 

Know how to interpret data and make it work for revenue growth?  It's one thing to create dashboards, and show trends, but it's another thing to really evaluate it, and make strategic decisions that can determine the right media, demand gen, and sales tactics that drive growth.  It's about data storytelling. My guest is Scott Taylor, known as “The Data Whisperer” who has helped countless companies by enlightening business executives to the strategic value of proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” As Principal Consultant for MetaMeta Consulting he helps Enterprises and Tech Brands tell their data story. An avid business evangelist and award-winning original thinker, he continually shares his passion for the strategic value of master data through industry events, public speaking, blogs, videos, whitepapers, podcasts, cartoons, puppets shows and all forms of thought leadership.

Check out "Telling Your Data Story" by Scott Taylor | https://amzn.to/3qaNakb Want to attend the Master Data Marathon 3.0 hosted by Scott Taylor? Use code MDM50 for 50% off right now! https://thinklinkers.com/events/master_data_marathon_2021 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Super exciting episode today. I got to interview Scott Taylor - The Data Whisperer. What a cool guy. We talked about data governance and data management. What are they? What does that even mean? We talked about Scott's decades of experience in the data industry and how his use of branding has helped him build his career. I'm always impressed with Scott's branding. Let's start with his name; the data whisperer. Great slogan, catchy, gives you an idea of what he's about. Then there's his truth hat, and we talk about that in the episode, and then he has puppets. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Want to break into data science? Check out my new course coming out later this summer: Data Career Jumpstart - https://www.datacareerjumpstart.com Want to leave a question for the Ask Avery Show? Written Mailbag: https://forms.gle/78zD544drpDAcTRV9 Audio Mailbag: https://anchor.fm/datacareerpodcast/message Want to be on The Ask Avery Show? Sign up for a spot here: https://calendly.com/datacareer/ask-avery?month=2021-05 Watch The Ask Avery Show Live Tuesday's at 8PM: https://www.datacareerjumpstart.com/AskAvery Add The Ask Avery Show to your calendar: https://calendar.google.com/calendar/ical/c_u2rk36mj5mgqg5g42glm9a741c%40group.calendar.google.com/public/basic.ics Subscribe on YouTube: https://www.youtube.com/channel/UCuyfszBAd3gUt9vAbC1dfqA --- Send in a voice message: https://anchor.fm/datacareerpodcast/message Support this podcast: https://anchor.fm/datacareerpodcast/support

“Data Whisperer” Scott Taylor is a speaker, author, and an industry leader in data management. He has taught many thought leaders the art and strategic value of data storytelling and provided many tools and techniques to do so in his book "Telling Your Data Story: Data Storytelling for Data Management." He has been a keynote speaker and host of many events, including Enterprise Data World and Master Data Marathon. In this episode, Scott discusses the key techniques that data management strategists and practitioners need to consider to make them successful and deliver value to the business. In addition, he will share some themes he outlines in his book. Want More? Scott Taylor’s book Telling Your Data Story: Data Storytelling for Data Management Learn about a Puppet Service Talk on Data Management LinkedIn Profile – https://www.linkedin.com/in/scottmztaylor/ The Data Whisperer YouTube Channel – https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw Too Much Tech Talk? (A puppet service announcement) – https://youtu.be/_JQ3HriEK0E Using the 3Vs of Big (Data) Storytelling: Vision, Vocabulary, Voice – https://issuu.com/infogovworld/docs/igw_vol_2_issue_2 MetaMeta Consulting – https://www.metametaconsulting.com/ Connect with our host Arvind Murali, Data Chief Strategist at Perficient Learn more about Perficient's Data + Intelligence expertise

This week we talk with Scott Taylor, also known as “The Data Whisperer.” Scott is a globally recognized thought leader and a consultant on the strategic value of proper data management. As Principal of MetaMeta Consulting, he provides Data Evangelism-as-a-Service to help enterprises and tech brands tell their data story by focusing on the WHY of business alignment rather than the HOW of technical implementation. He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble.We discuss how data storytelling is important to gain funding for initiatives, and why the data management community struggles to get the message across to the business. He shares some wisdom about how to craft effective stories, and even why he uses puppets on his YouTube channel.Scott Taylorhttps://www.linkedin.com/in/scottmztaylor/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

A chat with the Data Whisperer about the importance and value of proper data management. Scott offers his expertise by way of fun and creative Data Storytelling...a different type of storytelling...not a story WITH data but ABOUT the data to determine the truth in the data. "If you don't have the truth, you can't determine the meaning." - Scott TaylorScott Taylor, The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” As Principal Consultant for MetaMeta Consulting he helps Enterprises and Tech Brands tell their data story.An avid business evangelist and original thinker, he continually shares his passion for the strategic value of master data through industry events, public speaking opportunities, blogs, videos, whitepapers, podcasts, cartoons, puppets shows and all forms of thought leadership. His new book – TELLING YOUR DATA STORY: Data Storytelling for Data Management is available now.He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble.ABOUT THE BOOK – Telling Your Data Story- Data Storytelling for Data ManagementThe Data Whisperer’s practical guide to explaining and understanding the strategic value of data management. The need for data management is everywhere across your company. The value of every digitally transformative customer-facing initiative, every data science and analytics-based project, every as-a-service offering, every foray into e-commerce, and every enterprise software implementation is inextricably linked to the successful output of data management efforts. Although it is a simple function of garbage in garbage out, that slogan rarely drives any sustainable executive action. We need to tell a better data story.Data Storytelling is probably the hottest non-technical trend in the technology-related space. But it does not directly support data management because it is focused on analytics or telling stories with data. So, it is time to expand the realm of Data Storytelling to recognize the role of data management by telling stories about data.The book can be purchased from Technics Publications (also available on Amazon)Please use promo code DATAWHISPERER to save 20% when purchasing directly from the publisher sitehttps://technicspub.com/data-storytelling/Additional LinksToo Much Tech Talk?  (A puppet service announcement)Connecting Data Management to the Essence of Your BusinessData Has Got to Move to Have ValueThe Super Hero Adventures of **Master Data** Scott Taylor - The Data Whisperer YouTube Channel#data #datamanagement #puppets #creativedata #datastorytelling #metadataSubscribe to our podcast, and leave a reviewConnect with us on Instagram, FaceBook, Twitter , and LinkedInhttps://eima-inc.com/lets-talk-small-data@letstalksmalldatapodMusic credit: Yung Kartz

We catch up with Scott Taylor to learn more about his data whispering skills and insights. More about Scott via his Linkedin page -> https://www.linkedin.com/in/scottmztaylor/ Let me help you TELL YOUR DATA STORY I can be your voice for Data Management Partnering with Enterprises and innovative Data Brands that want to change the nature of data management - and help them tell their story! Too Much Tech Talk? (A puppet service announcement) Connecting Data Management to the Essence of Your Business https://www.youtube.com/watch?v=AIf7k6D68HU Buy the book Here - Telling Your Data Story - Data Storytelling for Data Management 20% off with code: DATAWHISPERER Scott was brought to you by Simon Cocking Irish Tech News.com in collaboration with DAMA Ireland. DAMA (International Data Management Association) is the premier international organisation for data management professionals. A new DAMA Ireland team led by Carl Kane is mobilising at the moment and are affiliating with DAMA International and its Certified Data Management Professionals wing. DAMA Ireland will aim to promote the understanding, development and practice of managing data and information as key enterprise assets to support organisations and personal development. Look out for more news and a relaunch of DAMA Ireland in H2 2021. Follow @CarlSugarKane and @DAMAIreland for updates. http://damaireland.org/

The concepts behind master data have been around for a very, very long time. Which means the businesses won’t function well without implementing master data. Scott Taylor, the Data Whisperer, believes that it is more productive to talk to management about data than the processes behind it. The business side is more interested in the WHY side of data. Why are you telling me about this? Why are we funding this? What does it matter to me? So there is always that gap between requirements/implementation versus strategy/rationale. Storytelling is very hot right now. But most of the storytelling is focused on data analytics, visualization, charts etc. But not many are focusing on storytelling of the data management itself. Telling stories of the data is as important as telling stories with data. Data management is about determining the truth. So instead of saying garbage in garbage out, be strategic about the gaps in that truth.

The concepts behind master data have been around for a very, very long time. Which means the businesses won't function well without implementing master data. Scott Taylor, the Data Whisperer, believes that it is more productive to talk to management about data than the processes behind it. The business side is more interested in the WHY side of data. Why are you telling me about this? Why are we funding this? What does it matter to me? So there is always that gap between requirements/implementation versus strategy/rationale. Storytelling is very hot right now. But most of the storytelling is focused on data analytics, visualization, charts etc. But not many are focusing on storytelling of the data management itself. Telling stories of the data is as important as telling stories with data. Data management is about determining the truth. So instead of saying garbage in garbage out, be strategic about the gaps in that truth.

Scott Taylor - The Data Whisperer (DATAcated Conference Feb 2021) --- Support this podcast: https://anchor.fm/datacated/support

Watch this episode on YouTube: https://youtu.be/Nm_qcKlSm1g This week we welcome back Scott Taylor, “The Data Whisperer,” for a discussion about data storytelling, the topic of his new book. Enjoy this fun and lively conversation! * Get the Data Leadership Book – https://dataleadershipbook.com * Data Leadership Lessons on YouTube – https://www.youtube.com/c/DataLeadershipLessons* Save 20% on your first order at the DATAVERSITY Training Center with promo code “AlgminDL” – https://training.dataversity.net/?utm_source=algmindl_res * Guest and Sponsorship Inquiries – podcast@algmin.com About Scott Taylor:Scott is a globally recognized thought leader and a consultant on the strategic value of proper data management. As Principal of MetaMeta Consulting, he provides Data Evangelism-as-a-Service to help enterprises and tech brands tell their data story by focusing on the WHY of business alignment rather than the HOW of technical implementation. He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble. – Book – “Telling Your Data Story” (Use promo code DATAWHISPERER for 20% off) – https://technicspub.com/data-storytelling/– MDM – Master Data Marathon 2.0 (Use promo code MDM20 for 20% off the ProPass) – https://www.thinklinkers.com/events/master-data-marathon– LinkedIn Profile – https://www.linkedin.com/in/scottmztaylor/– The Data Whisperer YouTube Channel – https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw– MetaMeta Consulting – https://www.metametaconsulting.com/

Learn more about data storytelling for data management from Scott Taylor - the Data Whisperer.

Did you know that 90% of the world's data actually was created in the last two years? Surprisingly, most of this is outside on the internet. Maven Data founder, Elisa Choy, described herself as a 'Data Whisperer' and is passionate about assisting business leaders to make decisions with confidence through the use of data. She shared with @Dawn the importance of understanding how to leverage your internal and external data to help your business tap its market and connect to its customers. A data analyst specialist, Elisa has worked for leading companies across Australia, including Woolworths, Caltex, and Seven West Media until starting her own data analysis companies: Strategic Data Central, and now, Maven Data, Australia's first AI-powered market research agency. In this episode of DAWNCast, Elisa shares with @Dai Le and @Cathy Ngo her accurate prediction of The Voice winner, storytelling through data, and the presence of social media. Timestamps: 00:00 Introduction 00:37 What is Maven Data? 02:40 How did Elisa get into data? 08:14 Australia lack of data agencies 09:44 Data in helping society 12:14 Everything is data 13:35 TikTok vs Facebook: Sharing data across social media 18:21 Market analysis and transformational narratives 21:01 Data through stories 21:50 Businesses listening to customers and data 24:26 What fuels Elisa? 25:55 Tips for small business owners 27:05 Influence of earlier experience 29:10 Dark moments: Bullying in the workplace 37:02 Mainstream Australian culture 39:55 Predicting the winner of The Voice 42:43 Understanding what people care about through data 46:32 Technology catching up to data 50:12 Will the economy grow again? 52:08 Global wellness trends _____________________________________________________________ CONNECT WITH US! DAWN is always eager to learn and share stories from different perspectives. If you have a story to share or know someone who is championing Inclusion & Diversity, please contact us! OUR WEBSITE - https://dawn.org.au/ FACEBOOK - https://www.facebook.com/dawnconnect/ TWITTER - https://twitter.com/yourdawn LINKEDIN - https://www.linkedin.com/company/dawn... INSTAGRAM - @dawn_podcast SOUNDCLOUD - https://soundcloud.com/dawnpodcast _____________________________________________________________ CONTACT US! What topics do you like to hear about? Do you have questions you like us to answer in our podcasts? Let us know! info@dawn.org.au

The topic of data is like a boomerang. It always seems to come back into every discussion when we get into the nuts and bolts of implementing a digital transformation in procurement or even just implementing a software solution to get more visibility into spend analytics. Problem is, investing in it often doesn't yield a visible payback that can be directly tracked to a future P&L statement. So, how can data management ever become top of the agenda? My guest today argues that a significant part of the solution is being able to tell the right story to the right people, to help them better understand the implications of NOT doing this. The message is clear. At the point of putting together a business case and a budget appropriation request for implementing procurement tech, getting your data ducks in a row needs to be an integral part of the calculation. Scott Taylor joins me on this week's podcast to help explain why. Why Implementing a Digital Procurement Solution Must Include A Data Strategy: Scott Taylor is The Data Whisperer1:47 What problems does Scott see when it comes to the causes and the effects of poor or inconsistent data? 5:53 Master data - what are the different types of data in the procurement space and where do the common pitfalls tend to come from? And how can feeding garbage into a procurement tech solution impact your implementation of a digital transformation? 8:46 Why is data management an important component in the various different procurement initiatives that are buzzwords at the moment? 12:02 Scott explains his "4C" concept and how it helps businesses to understand their potential flaws in master data management. 18:12 If we assume that cleaning your data is something that's a non-negotiable, I ask Scott how to approach the discussion with key decision makers. Specifically, how to pitch to CFOs to get buy-in to make the investment in something that doesn't have an immediate, demonstrable payback. 21:10 Scott explains why if digital transformation is part the journey of where a company wants to go, it requires highly structured data to successfully reach this destination. 22:11 Why selling data cleaning as a stand-alone project is likely to fail, and how to make the case for including data management and structure in the budget of any large-scale procuretech investment. 23:59 When it comes to data management, do smaller businesses have the advantage over larger corporations because they have fewer legacy systems and less data to manage, or do the larger businesses have the upper hand because they have the resources and expertise to stay one step ahead? 27:41 As a final question, I ask Scott about whether he thinks data scientists will be an integral part of procurement organisations going forward. How to connect with Scott: https://www.metametaconsulting.com (Meta Meta Consulting website) https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw (Scott's YouTube Channel) https://www.linkedin.com/in/scottmztaylor/ (Scott's LinkedIn profile) How to connect with James: https://jamesmeadsconsulting.com/ (James Meads Consulting website) https://linkedin.com/in/james-meads/ (James' LinkedIn profile) https://bookme.name/jamesmeads/lite/initial-consultation (Book a Call with James) https://linkedin.com/showcase/procuretechpodcast (Follow The Procuretech Podcast on LinkedIn)

In my third episode, I speak with Scott Taylor The Data Whisperer about Data Management and data storytelling. We discuss how companies should focus on their data fundamentals to manage their relationships and brands. Scott Taylor, known as The Data Whisperer, is a globally recognized thought leader and a consultant on the strategic value of proper data management. As Principal of MetaMeta Consulting, he provides Data Evangelism-as-a-Service to help enterprises and tech brands tell their data story by focusing on the WHY of business alignment rather than the HOW of technical implementation. He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble. About Samir: Samir is a data strategy and analytics leader, CEO and Founder of datazuum. He has a history of helping data executives and leaders craft and execute their data strategies. His passion for data strategy led him to launch, the Data Accelerator Workshop, and host the popular Data Strategy Show. After a career in both private and public sectors Samir launched the datazuum brand in 2012, with a view to working with executives to deliver data strategy at a time when data was not seen as a business asset. Today datazuum delivers projects across both private and public sectors including: Charities, Financial Services (Banking & Insurance), Government, Housing & Construction, Law Enforcement, Logistics, Media & Publishing, Outsourcing, Postal, Retail, Telecoms, Transport and Utilities. Samir has 20 years of international experience across Europe, North America, and Africa. Is a regular speaker at international conferences, coach / mentor, a charity fundraiser, and youth champion for Working Knowledge - supporting young people to achieve their personal and career goals in life. Samir lives in London with his wife and daughter. Contact details for Samir LinkedIn: Samir Sharma Email: samir@datazuum.com website: www.datazuum.com

Watch this episode on YouTube: https://youtu.be/a2TK0dLluag * Get the Data Leadership Book – https://dataleadershipbook.com * Data Leadership Lessons on YouTube – https://www.youtube.com/c/DataLeadershipLessons* Save 20% on your first order at the DATAVERSITY Training Center with promo code “AlgminDL” – https://training.dataversity.net/?utm_source=algmindl_res * Guest and Sponsorship Inquiries – podcast@algmin.com This week we talk with Scott Taylor, also known as “The Data Whisperer.” Scott is a globally recognized thought leader and a consultant on the strategic value of proper data management. As Principal of MetaMeta Consulting, he provides Data Evangelism-as-a-Service to help enterprises and tech brands tell their data story by focusing on the WHY of business alignment rather than the HOW of technical implementation. He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble. We discuss how data storytelling is important to gain funding for initiatives, and why the data management community struggles getting the message across to the business. He shares some wisdom about how to craft effective stories, and even why he uses puppets on his YouTube channel. DATAVERSITY Articles mentioned in the show:– Data Management has Failed! And Presented Us a Historic Opportunity – https://www.dataversity.net/data-management-has-failed-and-presented-us-an-historic-opportunity/– Data Management Hasn't Failed, but Data Management Storytelling Has – https://www.dataversity.net/data-management-hasnt-failed-but-data-management-storytelling-has/ For more information about Scott:– LinkedIn Profile – https://www.linkedin.com/in/scottmztaylor/– The Data Whisperer YouTube Channel – https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw– Too Much Tech Talk? (A puppet service announcement) – https://youtu.be/_JQ3HriEK0E– Using the 3Vs of Big (Data) Storytelling: Vocabulary, Voice and Vision – https://issuu.com/infogovworld/docs/igw_vol_2_issue_2– MetaMeta Consulting – https://www.metametaconsulting.com/

Today's guest is Scott Taylor, who is commonly known as "The Data Whisperer." Scott has helped countless companies “calm data down” by enlightening business executives to the strategic value of master data and proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” He also acts as Principal Consultant for MetaMeta Consulting – A Data Story Boutique. An avid business evangelist and original thinker, Scott continually shares his passion for the strategic value of master data through industry events, public speaking opportunities, blogs, videos, whitepapers, podcasts, cartoons, puppets shows and all forms of thought leadership. He has also worked with global enterprises by representing some of the world's most iconic business data brands including Dun & Bradstreet, Nielsen and Microsoft. In the episode, Scott will discuss: His interesting work in helping enterprises tell their data story, The role of Data Management within Data Storytelling, Challenges of introducing a data-driven culture in your business, How to effectively communicate with senior managers & stakeholders, The role of Data Monetization in impacting ROI, and What he loves about public speaking.

On this episode of The Artists of Data Science, we get a chance to hear from Scott Taylor, also known as the "Data Whisperer." He has spread the gospel of digital transformation through public speaking engagements, blogs, videos, white papers, podcasts, puppet shows, cartoons and all forms of verbal and written communications. He has also helped organizations, such as Microsoft and Nielsen, comb through and organize their data for meaningful use. Scott shares his "eight 'ates of master data", a set of rules to engage with master data in a meaningful way. He also goes over his tips for communicating with executives, along with important soft skills that are being overlooked by data scientists. Scott is very articulate, and his passion for data and teaching are definitely evident in this episode! WHAT YOU WILL LEARN [12:57] The eight 'ates of master data management [17:04] Data science communication with executives [21:45] Legacy data systems QUOTES [3:37] "It's not all about building. Sometimes it's about making sure things are structured and organized the right way." [7:11] "Hardware comes and goes. Software comes and goes. Data always remains." [16:11] "Data, to have value, has got to be in motion." [20:36] "If you're a data scientist, you are the business….and it's impossible for you to learn too much about your own business." [27:08] "…you've got to bring people from "I have no idea what you're talking about" to "how can we live without this?" and that comes from telling a good story." WHERE TO FIND SCOTT ONLINE LinkedIn: https://www.linkedin.com/in/scottmztaylor/ Twitter: https://twitter.com/stdatawhisperer Website: https://www.metametaconsulting.com/ SHOW NOTES [00:01:20] The introduction for our guest today [00:02:54] Scott talk to us a bit about his professional journey, how he got involved in the data world. And what drew him to this field? [00:04:40] Scott talks to us about some of the early gigs he had in the data space. [00:05:54] Where do you see kind of the field of big data and digital transformation? What's this landscape going to look like in two to five years? [00:07:41] Scott talks about how the stakes are changing and how data management is unavoidable [00:08:32] Scott goes more in-depth as to how the stakes are changing and how he's seen it play out across enterprise organizations. [00:09:56] In this vision of the future where the stakes are changing, what do you think is going to separate the great data professionals from the merely good ones? [00:11:25] Scott takes us through what he calls the "eight 'Ates" of data: Relate, Aggregrate, Validate, Integrate, Interoperate, Evaluate, Communicate, Circulate [00:16:29] Scott breaks down how to effectively communicate with executives and what they care about - hint: not necessarily what you care about as a data scientist [00:18:27] Scott shares some tips for data scientists coming into organizations with legacy organizations and how to navigate that landscape [00:21:11] What are the similarities or differences in the challenges a legacy system organization faces versus a tech startup? And how can one navigate these waves? [00:23:40] So what would you say is the biggest data blunder in the last year or two? He describes the system of hotel keys and how it relates to master data, very interesting! [00:25:12] So what about some data wonders? He describes an everyday application of a wonder: the checkout counter at a grocery store. [00:26:41] More insight on communicating with stakeholders and executives [00:27:56] What are some of the soft skills that that candidates are missing that are really going to separate them from the competition? [00:29:29] There's a lot of people out there who are trying to break into the data space and maybe they feel like they don't belong there or know enough for they aren't smart enough. Do you have any words of encouragement for them? [00:31:20] Scott does a deep dive into his passion for data and how you can cultivate it in yourself [00:33:02] What's the one thing you want people to learn from your story? [00:34:21] The lightning round Special Guest: Scott Taylor.

Hello Everyone, The guest we have today, Scott Taylor, he is a strategic advisor, master data storyteller, professional speaker and data management leader. He is known as "The Data Whisperer".Recently Ranked #1 Thought leader in Big Data space on Thinker 360. He has lot more to share about, master data, 4Cs and 5 Pillars of data as well as career and leadership. He has a very specific advise and said if you want to grow "Learn the business and Learn your Organization you are working in". You can find him on Linkedin as well as he has his Youtube Channel. Refer below - https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw https://www.linkedin.com/in/scottmztaylor/ Feel free to reach out to him, if you have any more questions. Watch complete episode - https://youtu.be/XgH2dKtQU5Q Listen to full episode - https://anchor.fm/vaishali-lambe/episodes/SoLeadSaturday---Episode-17---Scott-Taylor-datastoryteller-datamanagement-strategyadvisor-ec1n1b Hope you will enjoy this episode. Until we meet, Happy Leading and Let't Lead Together! Bye for Now. --- Support this podcast: https://anchor.fm/vaishali-lambe/support