What's New In Data

Modernizing databases in practice involves more than just moving data—it requires rethinking how systems, developers, and AI interact. In this episode, Shireesh Thota, Corporate Vice President of Azure Databases at Microsoft, joins Alok Pareek, co-founder and Executive Vice President of Product Development at Striim, to discuss the evolution of operational databases, the rise of real-time data...

What if the fastest route to real AI value isn’t training a new model—but learning how to use the ones we already have, better? We sit down with author and professor John K. Thompson to chart a clear path from AI’s roots to practical wins you can ship this quarter, while keeping an honest eye on what stands between today’s LLMs and true AGI.We start with the origin story—from Turing’s early ideas...

In this episode of What’s New in Data, we’re joined by Clare Liguori – Senior Principal Engineer at AWS – to dig into the evolving role of retrieval in modern AI systems. Clare unpacks why retrieval shouldn’t just be thought of as a technique to get documents — it’s a strategic tool that can unlock smarter, more adaptive agents.We also explore how AWS is thinking about orchestration, what...

Jonathan Shough, CIO of Parexel, joins us to talk about leading data modernization in one of the world’s most regulated industries. He shares how compliance can be reframed as an enabler, not a blocker—and why it’s critical to deliver value to patients, not just platforms. We get into Parexel’s pragmatic approach to AI adoption, the role of human interaction in digital transformation, and what it...

Joe Reis joins us to reflect on life after Fundamentals of Data Engineering, what makes data content worth consuming, and why good taste matters as much as technical skill. We talk about burnout in big tech, the myth of AI replacing everyone, and how Discord communities, DJ sets, and a sense of humor are helping shape the future of data. This one’s part industry pulse check, part real talk.Follow...

Barzan Mozafari, CEO of Keebo and former computer science professor, joins us to explore how AI is changing the way data teams work. We talk about the hidden inefficiencies in cloud data platforms like Snowflake and Databricks, how reinforcement learning can automate performance tuning, and why the tradeoff between cost and speed isn’t always what it seems. Barzan also shares thoughts on LLMs,...

What if your data pipeline could run 10x faster without the overhead? Jacopo Tagliabue, CTO of Bauplan and NYU adjunct professor, is pushing the boundaries of data infrastructure with lightweight DAGs, Apache Arrow, and a radically different take on functions as a service. In this episode, he breaks down the tech stack behind Bauplan and why the future of scalable data pipelines is all about...

Sol Rashidi has built AI, data, and digital strategies inside some of the world’s biggest companies—and she’s seen the same mistakes play out again and again. In this episode, she unpacks why AI initiatives often stall, how executives misread what “transformation” really requires, and why the future of AI success isn’t technical—it’s cultural. If you think AI is just a tech problem, Sol is here...

Spencer Cook, Lead Solutions Architect at Databricks, joins to unpack how enterprises are moving beyond hype and building practical AI systems using vector search, RAG, and real-time data pipelines. He and John Kutay get into what it really takes to serve production LLMs safely, avoid hallucinations, and tie AI back to business outcomes—without losing sight of governance, latency, or customer...

Peter Laflin, Chief Data Officer at Morrisons, shares how his team turned customer confusion into a cutting-edge vector search experience—bridging physical retail with AI-powered search. He and John Kutay dive into the practical challenges of implementing LLMs and real-time data pipelines at scale, the importance of starting with actual customer problems, and why the best engineering feels a...