The Analytics Engineering Podcast

Dr. Eirini Kalliamvakou is a senior researcher at GitHub Next. Eirini has built a career on studying software engineers, how to measure their productivity, how developer experience impacts productivity, and more. Recently, Eirini has been working on quantifying the impacts of GitHub Copilot. Does it actually help software engineers be more productive? Tristan and Eirini explore how to quantify developer productivity in the first place, and finally, arriving at whether or not Copilot‌ makes a difference. In the search for real business value, this research is a real bellwether of things to come. 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. Join data practitioners and data leaders this October in Las Vegas at Coalesce, the analytics engineering conference hosted by dbt Labs. Register now at coalesece.getdbt.com. Listeners of this show can use the code podcast20 for a 20% discount.

Yohei Nakajima is an investor by day and coder by night. In particular, one of his projects, an AI agent framework called BabyAGI that creates a plan-execute loop, got a ton of attention in the past year. The truth is that AI agents are an extremely experimental space, and depending on how strict you want to be with your definition, there aren't a lot of production use cases today.  Yohei discusses the current state of AI agents and where they might take us.  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.

Misha Panko has worked in data for a long time, including on high performance data teams at Uber and Google. Today, Misha is the co-founder and CEO of Motif Analytics, a product focused on helping growth and ops teams understand their event data. In this episode, Tristan and Misha nerd out about the state of the art in computational neuroscience, where Misha got his PhD. They then go deep into event stream data and how it differs from classical fact and dimension data, and why it needs different analytical tools. Make sure to check out the back half of the episode, where they dive into AI and how Motif is applying breakthroughs in language modeling to train foundation models of event sequences—check out his team’s blog post on their work. 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.

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.

Jonathan Frankle is the Chief Scientist at MosaicML, which was recently bought by Databricks for $1.3 billion.  MosaicML helps customers train generative AI models on their data. Lots of companies are excited about gen AI, and the hope is that their company data and information will be what sets them apart from the competition.  In this conversation with Tristan and Julia, Jonathan discusses a potential future where you can train specialized, purpose-built models, the future of MosaicML inside of Databricks, and the importance of responsible AI practices. 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.

In this conversation with Tristan recorded at Coalesce 2023, Kasey Mazza, an analytics engineering manager on the RevOps team at HubSpot, discusses the roles of data analysts and analytics engineers, the importance of building internal data communities, and the evolving landscape of data teams.  Watch Kasey’s Coalescse 2023 presentation The career growth software development lifecycle. 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.

It turns out data plays a big role in getting cereal manufactured and delivered so you can enjoy your Cheerios reliably for breakfast. We talk with Arjun Narayan, CEO of Materialize, a company building an operational warehouse, and Nathan Bean, a data leader at General Mills responsible for all of the company's manufacturing analytics and insights.  We discuss Materialize’s founding story, how streaming technology has matured, and how exactly companies are leveraging their warehouse to operationalize their business—in this case, at one of the largest consumer product companies in the United States.  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.

Yannick Misteli is the head of engineering for the go-to-market domain at Roche, a $250 billion multinational pharmaceutical and diagnostics company.  Roche was an early supporter of dbt Cloud, and Yannick helped move his team of 120+ engineers to a modern data stack. He always finds a way to push the boundaries to make a large company founded in 1896 incredibly modern and innovative. We wanted to know more about the "how" of the work—the people, process, and technology.  Read more about Roche's data journey here: https://docs.getdbt.com/blog/dbt-squared