418 afleveringen
- The data industry rarely moves in a straight line. We swing from centralized to decentralized, batch to real-time, general-purpose to specialized, abstraction to control, and governance to self-service.
In this episode, I unpack why these cycles keep repeating, what forces push the pendulum in each direction, and why every successful architecture eventually creates the conditions for its own backlash. - We see a lot of hype cycles in our industry - Data mesh. Generative AI. Agents. Now context.
Every cycle brings a new label and a familiar promise: this will finally make your organization’s data useful.
The technology has improved enormously. So why do the same problems keep coming back?
In this episode, I explore how communication, incentives, and organizational politics shape what our tools actually deliver. Will context finally deliver the silver bullet to solve our problems? Is buying the next platform easier than resolving the messy organizational problems we all deal with? Listen to get my thoughts. Designing the AI-Driven Data Foundations: Architecture, Principles, and Practice w/ Sanjeev Mohan
18-09-2026 | 1 u.Former Gartner VP Analyst and principal at SanjMo, Sanjeev Mohan, joins me to break down the reality of AI adoption, data foundations, and why enterprises are hitting roadblocks with agents and LLMs. From comparing the current AI boom to the dot-com era to unpacking his new concept, ECL (Extract, Context, Link), Sanjeev explains why moving data around is no longer viable and why "there is no AI stack, only one stack." We also dive into capability overhang, artificial guardrails, the race to standardize semantic context, and why writing books and understanding core primitives still matter in the age of generative models- This week at dbt Summit, Tristan Handy (co-founder of dbt) asked me why I write books. It's a good question, especially today when reading is declining and any answer is seemingly at your fingertips.
In this Freestyle Friday, I discuss why I write books, why they still matter, and much more. If you're interested in writing a book, this episode is definitely a must-listen.
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Over The Joe Reis Show
I’m Joe Reis, co-author of Fundamentals of Data Engineering, creator of Mixed Model Arts, international speaker, and long-time observer of the tech industry’s favorite recurring mistakes.
Weekly broadcasts from somewhere on the road. Expect raw solo rants and long-form conversations with the engineers and leaders actually building things. I dive into data, AI, architecture, and career survival.
This podcast is invitation-only. Unsolicited guest pitches and PR outreach are not considered.
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