Eric Avidon is a journalist at TechTarget who's interviewed Tristan a few times, and now Tristan gets to flip the script and interview Eric. Eric is a journalist veteran, covering everything from finance to the Boston Red Sox, but now he spends a lot of time with vendors in the data space and has a broad view of what's going on. Eric and Tristan discuss AI and analytics and how mature these features really are today, data quality and its importance, the AI strategies of Snowflake and Databricks, and a lot more. Plus, part way through you can hear Tristan reacting to a mild earthquake that hit the East Coast.

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

Barry McCardel is the co-founder and CEO of Hex. Hex is an analytics tool that's structured around a notebook experience, but as you'll hear in the episode, goes well beyond the traditional notebook.

We're big fans of Hex at dbt Labs, and use it for a bunch of our internal data work. In this episode, Barry and Tristan discuss notebooks and data analysis, before zooming out to discuss the hype cycle of data science, how AI is different, the experience of building AI products, and how AI will impact data practitioners.

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

Matt Turck has been publishing his ecosystem map since 2012. It was first called the Big Data Landscape. Now it’s the Machine Learning, AI & Data (MAD) Landscape.

The 2024 MAD Landscape includes 2,011(!) logos, which Matt attributes first a data infrastructure cycle and now an ML/AI cycle. As Matt writes, “Those two waves are intimately related. A core idea of the MAD Landscape every year has been to show the symbiotic relationship between data infrastructure, analytics/BI, ML/AI, and applications.”

Matt and Tristan discuss themes in Matt's post: generative AI’s impact on data analytics, the modern AI stack compared to the modern data stack, and Databricks vs. Snowflake (plus Microsoft Fabric).

For full show notes and to read 7+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

Matthew Lynley is a bit of a hybrid. He's been a long-time journalist covering enterprise tech, currently in his fantastic AI and data newsletter Supervised, and he's also been a hands-on data practitioner.

Matthew has covered the analytics tech stack, but this time Tristan turns the tables to get Matthew’s perspective on the rise of Gen AI as a topic in the popular press, what's going on in the space today, and where AI is headed.

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

Juan Sequeda is a principal data scientist and head of the AI Lab at data.world, and is also the co-host of the fantastic data podcast Catalog and Cocktails.

This episode tackles semantics, semantic web, Juan’s research in how raw text-to-SQL performs versus text-to-semantic layer, and where we both believe AI will make an impact in the world of structured data analytics.

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

Benn Stancil, cofounder and CTO at Mode, returns to The Analytics Engineering Podcast to discuss the evolution of the term "modern data stack" and its value today. Tristan wrote on this idea for The Analytics Engineering Roundup in Is the Modern Data Stack Still a Useful Idea?

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

Moritz Heimpel from Siemens and Ben Flusberg from Cox Automotive have very similar jobs. They both act as stewards of the data strategies at large, complex companies.

In this episode, we get into what it’s like to collaborate with data at scale. Ben and Mortitz share their experiences adopting a data mesh architecture and what that looks like at their organizations.

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.

If Data Vault is a new term for you, it’s a data modeling design pattern. We’re joined by Brandon Taylor, a senior data architect at Guild, and Michael Olschimke, who is the CEO of Scalefree—the consulting firm whose co-founder Dan Lindstedt is credited as the designer of the data vault architecture. 

In this conversation with Tristan and Julia, Michael and Brandon explore the Data Vault approach among data warehouse design methodologies. They discuss Data Vault’s adoption in Europe, its alignment with data mesh architecture, and the ongoing debate over Data Vault vs. Kimball methods. 

For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

The Analytics Engineering Podcast is sponsored by dbt Labs.