Data Masters is the go-to place for data enthusiasts. We speak with data leaders from around the world about data, analytics, and the emerging technologies and techniques data-savvy organizations are tapping into to gain a competitive edge. Our experts also share their opinions and perspectives about the hyped, or overhyped, industry trends we may all be geeking out over.
Data Masters Podcast
Claim This Podcastby TAMR
5.0(19 reviews)
63 episodes
Updated Bi-weekly
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36
Podcast Authority
BetaPoorBased on show quality, social media presence, reviews, charts, and more
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Engagement51
Podcast Overview
Data Masters is the go-to place for data enthusiasts. We speak with data leaders from around the world about data, analytics, and the emerging technologies and techniques data-savvy organizations are tapping into to gain a competitive edge. Our experts also share their opinions and perspectives about the hyped, or overhyped, industry trends we may all be geeking out over.
Language
🇺🇲
Publishing Since
5/11/2020
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Recent Episodes
May 27, 2026
Why Context Is the New Currency in Data Strategy with Chris Tabb of LEIT DATA
<p><span style="background-color: transparent; color: rgb(22, 14, 61);">Data strategy is shifting upstream, moving from how organizations visualize data to the data that supplies those visualizations. In this episode, </span><a href="https://www.linkedin.com/in/chris-tabb-mean-data-streets/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Chris Tabb</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, Co-Founder and Chief Commercial Officer of </span><a href="https://www.linkedin.com/company/leit-data/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">LEIT DATA</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, joins us to explore why traditional ROI thinking fails data teams, how the friction framework changes how organizations build business cases and what the emerging context layer means for AI-ready data architectures.</span></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">KEY TAKEAWAYS</strong></p><p><br></p><p>00:00 Introduction. </p><p>02:50 Dashboards only create value when they drive a clear business decision. </p><p>05:15 Data strategy is shifting from visualization back toward the quality of the underlying data. </p><p>13:30 Business value is a positive evidence effect on business objectives, not a bottom-line metric.</p><p>15:10 Friction, measured by time, effort and frequency, is the foundation for a data business case.</p><p>17:00 Force multipliers solve a problem once and yield compounding returns across the organization.</p><p>22:10 Reading the annual report first will anchor any data project to the business's actual objectives.</p><p>26:30 The context layer unifies ontologies, knowledge graphs, semantic layers and vector databases under one concept.</p><p>28:30 Scoring and tuning prompt context is how organizations get more accurate, consistent AI outputs.</p><p>35:10 Meta metadata, data about the data about the data, is where enterprise value now lives.</p><p><br></p><p><span style="background-color: transparent;">Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.</span></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">RESOURCES MENTIONED</strong></p><p><br></p><p>Chris Tabb:</p><p><a href="https://www.linkedin.com/in/chris-tabb-mean-data-streets/" target="_blank">https://www.linkedin.com/in/chris-tabb-mean-data-streets/</a></p><p><br></p><p>LEIT DATA LinkedIn:</p><p><a href="https://www.linkedin.com/company/leit-data/" target="_blank">https://www.linkedin.com/company/leit-data/</a></p><p><br></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">LEIT DATA website:</span></p><p><a href="https://leit-data.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://leit-data.com/</a></p><p><br></p><p><span style="background-color: transparent;">O'Reilly book by Joe Reis and Matt Housley [Fundamentals of Data Engineering]:</span></p><p><a href="https://www.amazon.com/Fundamentals-Data-Engineering-Robust-Systems/dp/1098108302" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.amazon.com/Fundamentals-Data-Engineering-Robust-Systems/dp/1098108302</a></p><p><br></p><p><br></p><p><span style="background-color: transparent;">#DataStrategy #DataManagement #DataMastersPodcast</span></p>
April 15, 2026
Applying the Scientific Mindset to Machine Learning, Data Science and AI with Jonathan Burley of Bloomberg Industry Group
<p><span style="background-color: transparent; color: rgb(22, 14, 61);">Building effective AI products isn't just about using the latest large language model; it's about asking the right questions and solving real problems. In this episode, we’re joined by</span><a href="https://www.google.com/search?q=https://www.linkedin.com/in/jonathanburley/" target="_blank" style="background-color: transparent; color: rgb(22, 14, 61);"> </a><a href="https://www.google.com/search?q=https://www.linkedin.com/in/jonathanburley/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Jonathan Burley</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, Director of AI of </span><a href="https://www.linkedin.com/company/bloomberg-industry-group/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Bloomberg Industry Group</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, to explore his journey from modeling climate systems to leading AI strategy. Jonathan discusses why the scientific mindset is critical in machine learning, the value of the minimum viable experiment and how to avoid the pitfalls of generative AI demos.</span></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">Key Takeaways:</strong></p><p><br></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">00:00 Introduction.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">03:14 The evergreen skills of handling data nuances help scientists transition into industry.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">08:57 The scientific method provides a foundational mindset for reasoning under uncertainty.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">16:39 Frame conversations around concrete business problems instead of leading with new technology.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">19:46 Focus on minimum viable experiments to test core assumptions before committing to a minimum viable product.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">24:46 Find unexciting areas of the economy where AI tools can deliver rapid and measurable ROI.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">38:20 Approach generative AI demos with caution because they easily disguise incomplete products.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">41:51 Solve the most boring, thankless and repetitive tasks to build tools experts actually want to use.</span></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">Resources Mentioned:</strong></p><p><br></p><p><a href="https://www.google.com/search?q=https://www.linkedin.com/in/jonathanburley/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Jonathan Burley</a></p><p>https://www.google.com/search?q=https://www.linkedin.com/in/jonathanburley/</p><p><br></p><p><a href="https://www.linkedin.com/company/bloomberg-industry-group/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Bloomberg Industry Group</a> | LinkedIn</p><p>https://www.linkedin.com/company/bloomberg-industry-group/</p><p><br></p><p><a href="https://www.bloombergindustry.com/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Bloomberg Industry Group</a> | Website</p><p>https://www.bloombergindustry.com/</p><p><br></p><p><a href="https://www.actif.ai/index.html" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Actifai</a> | Website</p><p>https://www.actif.ai/index.html</p><p><br></p><p><a href="https://www.youtube.com/c/ContinuousDelivery" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Continuous Delivery — David Farley</a></p><p>https://www.youtube.com/c/ContinuousDelivery</p><p><br></p><p><br></p><p><br></p><p><span style="background-color: transparent;">Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.</span></p><p><br></p><p><br></p><p><span style="background-color: transparent;">#DataStrategy #DataManagement #DataMastersPodcast</span></p>
March 9, 2026
Bridging the Gap Between Engineering and Business Strategy with Dr. Elena Alikhachkina
<p><span style="background-color: transparent; color: rgb(22, 14, 61);">AI is not a side project; it is a business model shift. In this episode, we’re joined by </span><a href="https://www.linkedin.com/in/dr-elena-alikhachkina-2265041/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Dr. Elena Alikhachkina</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, Chief Data and AI Officer of </span><a href="https://www.linkedin.com/company/te-connectivity/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">TE Connectivity</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, director, board advisor and author, to explore why AI demands a product mindset, how “learning data” powers continuous AI loops and what boards must do now to govern AI responsibly. Elena shares why technical skills alone are no longer enough, how trust is being redefined in the age of digital employees, and why 2026 will mark a turning point for data, governance and enterprise transformation.</span></p><p><br></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">Elena challenges the idea that data is “the new oil” and instead reframes it as a living, learning asset embedded in business processes. We unpack what it really means to build AI loops, why product leaders must be deeply embedded in operations and how governance, data readiness and performance accountability must evolve as agents join the workforce.</span></p><p><br></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">Show Notes [shortened for website]:</strong></p><p><br></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">In this episode, we’re joined by </span><a href="https://www.linkedin.com/in/dr-elena-alikhachkina-2265041/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Dr. Elena Alikhachkina</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, Chief Data and AI Officer of </span><a href="https://www.linkedin.com/company/te-connectivity/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">TE Connectivity</a><span style="background-color: transparent; color: rgb(22, 14, 61);">, director, board advisor and author, to discuss why AI requires a product mindset, how learning data fuels continuous AI loops and what boards must do to govern AI responsibly. She explains why technical skills alone are not enough, how trust is changing in the era of digital employees and why 2026 will be a turning point for data and enterprise transformation.</span></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">Key Takeaways:</strong></p><p><br></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">00:00 Introduction.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">02:38 AI is reshaping data careers and elevating product and business skills.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">06:00 Product leaders go beyond dashboards to uncover the real business problem.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">09:43 Data teams must embed in operations and “walk the floor” to drive adoption.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">13:33 Data is not oil — it must power continuous learning loops.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">16:15 AI pilots fail when they do not close the loop with user feedback and new data.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">20:20 Boards face confusion and must translate AI into governance responsibilities.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">23:00 Data governance and data readiness must become board-level metrics.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">25:00 Leaders will manage digital employees and agents alongside humans.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">28:21 2026 will move AI beyond chat interfaces into embedded enterprise systems.</span></p><p><span style="background-color: transparent; color: rgb(22, 14, 61);">30:50 The AI opportunity is underestimated, but security and compliance may slow scale.</span></p><p><br></p><p><br></p><p><strong style="background-color: transparent; color: rgb(22, 14, 61);">Resources Mentioned:</strong></p><p><br></p><p><a href="https://www.linkedin.com/in/dr-elena-alikhachkina-2265041/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Dr. Elena Alikhachkina</a></p><p>https://www.linkedin.com/in/dr-elena-alikhachkina-2265041/</p><p><br></p><p><a href="https://www.linkedin.com/company/te-connectivity/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">TE Connectivity</a> | LinkedIn</p><p>https://www.linkedin.com/company/te-connectivity/</p><p><br></p><p><a href="https://www.linkedin.com/company/te-connectivity/" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">TE Connectivity</a> | Website</p><p>https://www.linkedin.com/company/te-connectivity/</p><p><br></p><p><a href="https://www.re-coded.com" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Re:Coded Newsletter</a></p><p>https://www.re-coded.com</p><p><br></p><p><a href="https://www.nacdonline.org" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">National Association of Corporate Directors</a> | Website</p><p>https://www.nacdonline.org</p><p><br></p><p><a href="https://www.jnj.com" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">Johnson and Johnson</a> | Website</p><p>https://www.jnj.com</p><p><br></p><p><br></p><p><br></p><p><span style="background-color: transparent;">Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.</span></p><p><br></p><p><br></p><p><span style="background-color: transparent;">#DataStrategy #DataManagement #DataMastersPodcast</span></p>
63 total episodes available
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