Data Faces is a data, analytics, AI, and marketing podcast that brings the human stories behind the numbers to the forefront. Hosted by David Sweenor — author and founder of TinyTechGuides — each episode features engaging conversations with the industry's leading voices: the data leaders, analytics practitioners, AI innovators, and marketing leaders shaping the future of data-driven decision-making. We explore the culture, challenges, and real-life experiences of the people behind the numbers — enterprise AI adoption, data governance, generative AI, analytics, and B2B marketing.
Data Faces Podcast
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42 episodes
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Podcast Authority
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Podcast Overview
Data Faces is a data, analytics, AI, and marketing podcast that brings the human stories behind the numbers to the forefront. Hosted by David Sweenor — author and founder of TinyTechGuides — each episode features engaging conversations with the industry's leading voices: the data leaders, analytics practitioners, AI innovators, and marketing leaders shaping the future of data-driven decision-making. We explore the culture, challenges, and real-life experiences of the people behind the numbers — enterprise AI adoption, data governance, generative AI, analytics, and B2B marketing.
Language
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Publishing Since
1/8/2025
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Podcast Authority
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Recent Episodes
June 30, 2026
The three V's of agentic AI | Doug Laney on the self-driving business
<p>Doug Laney coined the three V's of big data in 2001. On this episode of the Data Faces podcast, he names the next three for the agentic AI era: volition, visibility, and viscosity.<br>David Sweenor and Doug Laney get into the seven levels of agentic autonomy, from a basic chatbot to a business that runs itself, why labor savings are the least imaginative way to value an AI agent, who really owns your data, and what it would take for a billion-dollar company to run on a handful of people.<br>Doug Laney is the Innovation Fellow for Data and Analytics Strategy at West Monroe, author of Infonomics and Data Juice, and a former Gartner Distinguished Analyst.<br>Key takeaways:<br>- The three new V's of agentic AI: volition, visibility, and viscosity- The seven levels of agentic AI autonomy, and where most companies actually sit- Substitution, amplification, and invention: a better way to value agents- Warranted delegation over blind trust, the brakes before the accelerator- Why data is the strangest and most renewable asset a company owns<br>Chapters:<br>- 00:00 Intro- 01:55 The Risky Business icebreaker- 04:05 Do the original 3 V's still hold up?- 04:30 The new three V's: volition, visibility, viscosity- 07:06 Why labor savings are the least imaginative measure- 09:43 The hospital example: substitution, amplification, invention- 11:23 Cost versus revenue, and the numerator with no ceiling- 13:44 What MBA students grasp that executives miss- 17:27 Who really owns your data- 20:18 The seven levels of autonomy- 25:47 The billion-dollar company with almost no employees- 29:58 Warranted delegation and the brakes- 33:04 Parting wisdom from Marvin Minsky<br>Read the full blog post:https://tinytechguides.com/blog/data-faces-douglas-laney-ep42-three-vs-agentic-ai/?utm_source=youtube&utm_medium=video&utm_campaign=ep42-douglas-laney&utm_content=description<br>Connect with Doug Laney:LinkedIn: https://www.linkedin.com/in/douglaney<br>Listen to the Data Faces podcast:YouTube: https://www.youtube.com/playlist?list=PLzrDACjTQ4OBoQ8qM1FMGBwYdxvw9BurRSpotify: https://open.spotify.com/show/6SmGkQGvZQSAT1O7g1l2yFApple Podcasts: https://podcasts.apple.com/us/podcast/data-faces-podcast/id1789416487Amazon Music: https://music.amazon.com/podcasts/8465f3b3-5d41-4c84-a561-bf8af09560e3/data-faces-podcast<br>#agenticAI #AIagents #dataStrategy #infonomics #DataFaces<br></p>
June 16, 2026
The Question That Separates AI Value From Sunk Cost | Andreas Welsch
<p>Everyone is racing to do something with agentic AI. Almost nobody is asking whether they should. Andreas Welsch spent close to two decades building enterprise AI at SAP, and he is now one of the most direct voices on what agentic AI demands from business leaders.In this episode of the Data Faces Podcast, David Sweenor and Andreas Welsch talk about the contagion driving AI layoffs, the revenue question leaders keep skipping, the truth about "SaaS is dead," and why agent risk compounds as you add more agents. It is a candid conversation about keeping human judgment in the loop while the hype runs ahead of reality.Key takeaways1. AI layoffs spread like a contagion, one announcement at a time, even when the value case is unproven.2. The question that saves money and sanity is "should we?" not "can we?"3. Rebuilding SaaS yourself is possible, but you pay subscriptions for convenience, maintenance, and peace of mind.4. The bigger prize is revenue and growth, not another round of cost cuts.5. Agentic AI is a probabilistic system that can be confidently wrong, and risk compounds as agents multiply.Chapters (estimated from the transcript, verify against the recording)- 00:00 Intro- 01:01 What Intelligence Briefing does- 01:48 From pediatrician dreams to taking apart RC cars- 03:45 Leaving SAP and becoming the CXO of everything- 10:40 The layoffs vicious cycle and the revenue question- 13:58 Pilots versus production- 21:37 "SaaS is dead" and vibe-coding clones of DocuSign and Mentimeter- 25:00 When to defer risk to a vendor- 27:57 Just because you can does not mean you should- 32:47 Editing a book with three custom GPTs- 36:12 The conventional wisdom that is wrongLinksRead the full blog: https://tinytechguides.com/blog/andreas-welsch-agentic-ai-human-edge/?utm_source=youtube&utm_medium=video&utm_campaign=ep41-andreas-welsch&utm_content=description Connect with Andreas Welsch: https://www.linkedin.com/in/andreasmwelsch Intelligence Briefing: https://intelligence-briefing.com</p>
June 2, 2026
Forget AGI. Your AI Is Dumb Without Your Data | Josh Howard, Databricks
<p>"Without context, your agents are dumb." That's how Josh Howard, Senior Director of Product Marketing for Executive Audiences at Databricks, closed Episode 40 of the Data Faces Podcast.Frontier models are some of the most advanced technology of our lifetime. They are also dumb in the way that matters for your business, because they were trained on the public internet and have never seen your customer records, your forecast methodology, or your sales policies. In this episode, host David Sweenor and Josh Howard unpack new findings from the Databricks and Economist Enterprise *Making AI Deliver* survey of 1,221 senior technology leaders, including the 84/43 measurement gap, why data infrastructure costs more than the GPU bill, where AI agents are already working in the enterprise, and why the real race over the next five years isn't to AGI.**Key Takeaways:**1. Today's models are "dumb" not because they lack capability, but because they lack enterprise context2. 59% of senior tech leaders say data storage and movement is the biggest AI cost, only 25% say compute3. 84% of executives say AI is beating expectations, but only 43% require teams to measure the impact4. AI agents now create 80% of new databases on Databricks' Neon serverless Postgres layer, up from 0.1% in 20235. The next five years will reward boring work: cleaning data, fixing semantics, and tying agent projects to measurable outcomes**Timestamps:**00:00 - Opening and introduction01:17 - Josh's role leading PMM for executive audiences at Databricks02:21 - If not PMM: full-time fly-fishing guide in Colorado03:23 - "Your AI is dumb" — what the phrase actually means05:25 - Structured vs. unstructured data and the industry's row-and-column trap06:20 - Where Josh and Dave first met at Dell Technologies08:13 - Metadata, context, and the 20-year-old enterprise architect fight09:37 - The November 2022 ChatGPT moment in the C-suite11:07 - Trying to pry Excel from a financial analyst's hands at Alteryx12:08 - Human-in-the-loop and the Replit agent that wiped a production database12:53 - Conversational analytics, Databricks Genie, and internal semantics19:11 - Inside the Databricks and Economist *Making AI Deliver* survey20:54 - The 84/43 measurement gap23:21 - The 59/25 cost split — data infrastructure vs. compute28:30 - Upskilling, prompt engineer hype, and behavior change30:17 - AI washing on the 101 corridor and Allbirds' pivot to NewBird AI33:26 - What will look obvious in 202735:39 - Closing thought: "Without context, your agents are dumb"**More insights and resources:**Blog: https://tinytechguides.com/blog/forget-agi-your-ai-is-dumb-without-your-data/?utm_source=youtube&utm_medium=video&utm_campaign=ep40-josh-howard&utm_content=description Survey: https://www.databricks.com/resources/analyst-research/making-ai-deliver**Connect with Josh Howard:**LinkedIn: https://www.linkedin.com/in/joshoward/Databricks: https://www.databricks.com/Drop your thoughts in the comments!Like, share, and subscribe for more insights.#AgenticAI #EnterpriseAI #DataLeadership #Databricks #DataFacesPodcast</p>
42 total episodes available
Recent guests on Data Faces Podcast
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Judit Szabo
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Hyoun Park
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Shane Murray
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