The Analytics Engineering Podcast

Mike Stonebraker is a veritable database pioneer and a Turing Award recipient. In addition to teaching at MIT, he is a serial entrepreneur and co-creator of Postgres. Andy Palmer is a veteran business leader who serves as the CEO of Tamr, a company he co-founded with Mike. Through his seed fund Koa Labs, Andy has helped found and/or fund numerous innovative companies in diverse sectors, including health care, technology, and the life sciences.  In this conversation with Tristan and Julia, Mike and Andy take us through the evolution of database technology over 5+ decades. They share unique insights into relational databases, the switch from row-based to columnar databases, and some of the patterns of database adoption they see repeated over time. 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.

Wes McKinney is the creator of pandas, co-creator of Apache Arrow, and now Co-founder/CTO at Voltron Data. In this conversation with Tristan and Julia, Wes takes us on a tour of the underlying guts, from hardware to data formats, of the data ecosystem. What innovations, down to the hardware level, will stack to lead to significantly better performance for analytics workloads in the coming years? To dig deeper on the Apache Arrow ecosystem, check out replays from their recent conference at https://thedatathread.com. 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.

Product experimentation is full of potholes for companies of any size, given the number of pieces (tooling, culture, process, persistence) that need to come together to be successful. Vijaye Raji (currently Statsig, formerly Facebook + Microsoft) and Sean Taylor (currently Motif Analytics, formerly Facebook + Lyft) have navigated these failure modes, and are here to help you (hopefully) do the same. This convo with Tristan + Julia is light on tooling + heavy on process: how to watch out for spillover effects in experiments, avoiding bias, how to run an experiment review, and why experiment throughput is a better indicator of success than individual experiment results. 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.

Stephen Bailey, data engineer at Whatnot and writer of an incredibly entertaining data substack, discusses the challenges of being a generalist in the data field. They explore the supportive dbt community and the importance of collaboration. They also discuss gaining unique perspectives, finding creative expression, and their hopes for the future of the data community.

WARNING: This episode contains detailed discussion of data contracts. The modern data stack introduces challenges in terms of collaboration between data producers and consumers. How might we solve them to ultimately build trust in data quality? Chad Sanderson leads the data platform team at Convoy, a late-stage series-E freight technology startup. He manages everything from instrumentation and data ingestion to ETL, in addition to the metrics layer, experimentation software and ML.  Prukalpa Sankar is a co-founder of Atlan, where she develops products that enable improved collaboration between diverse users like businesses, analysts, and engineers, creating higher efficiency and agility in data projects.  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.

Abhi is a growth and data leader, and an excellent Twitter follow. Most recently, he was Head of Growth and Analytics at Flexport, where he helped the company to grow 10x over the past 3 years. Previously, Abhi led growth and data teams at Keap, Hustle, and Honeybook. In this conversation with Tristan and Julia, Abhi explains his methodology for setting up a new growth data organization, and how you might be falling victim to the dreaded "arbitrary uniqueness" bug. 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

Katie was a founding member of Reddit's data science team and, currently, as Twitter’s Data Science Manager, she leads the company’s infrastructure data science and analytics organization. In this conversation with Tristan and Julia, Katie explores how, as a manager, to help data people (especially those new to the field!) do their best 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.

As Head of Analytics at Clearbit, Julie serves as a data team of one in a 200+ person company (wow!). In this conversation with Tristan and Julia, Julie dives into how she's helped Clearbit implement data activation throughout the business, and realize the glorious dream of self-serve 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.

Jordan Tigani is an expert in large-scale data processing, having spent a decade+ in the development and growth of BigQuery, and later SingleStore. Today, Jordan and his team at MotherDuck are in the early days of working on commercial applications for the open source DuckDB OLAP database. In this conversation with Tristan and Julia, Jordan dives into the origin story of BigQuery, why he thinks we should do away with the concept of working in files, and how truly performant “data apps” will require bringing data to an end user’s machine (rather than requiring them to query a warehouse directly).

Matt Bornstein and Jennifer Li (and their co-author Martin Casado) of a16z have compiled arguably the most nuanced diagram of the data ecosystem ever made.  They recently refreshed their classic 2020 post, "Emerging Architectures for Modern Data Infrastructure" and in this conversation, Tristan attempts to pin down: what does all of this innovation in tooling mean for data people + the work we're capable of doing? When will the glorious future come to our laptops? 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.