The Analytics Engineering Podcast

In this talk, former podcast guest Benn Stancil walks through what he believe the next evolution of the modern data stack should look like - and more importantly, how those who use it should experience it.

Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com.

The Analytics Engineering Podcast is brought to you by dbt Labs.

Where does Snowflake go from here? What meta trends and technologies play into that vision? How does that impact the world of data analytics?

Christian and Tristan have no shortage of opinions or ideas. This is your chance to hear some of them, live and unfiltered.

Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com.

The Analytics Engineering Podcast is brought to you by dbt Labs.

Reynold Xin is a technical co-founder and Chief Architect at Databricks. He's also a co-creator and the top contributor to the Apache Spark project.

In this casual conversation with Drew Banin, co-founder and Chief Product Officer at dbt Labs, the two will be discussing the data infrastructure trends they find most interesting.

Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com.

The Analytics Engineering Podcast is brought to you by dbt Labs.

The modern data stack is the third generation of data analysis products to come to prominence since the 90's. The prior waves—data warehouse appliances and then Hadoop—were both big steps forwards but ultimately failed to live up to their initial promise.

Is the modern data stack just another iteration in a long string of "trendy technologies" in data––waves that crash upon the shore but ultimately recede? Or is it somehow more permanent?

Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com.

The Analytics Engineering Podcast is brought to you by dbt Labs.

What is it like to build a data team for a company in the data space?

This talk is centered around how dbt Labs is building their data team. We will cover how our team is structured, how we operate and interact with the greater organization, and how we set expectations and responsibilities that are helping us become a self-service organization.

Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesce.getdbt.com.

The Analytics Engineering Podcast is brought to you by dbt Labs.

As a product leader at companies like Heroku and Zendesk, DeVaris specialized in building infrastructure-grade products. Currently, as the CEO of Meroxa, he enables teams to build real-time data infrastructure with the same ease as we now take for granted in batch.

In this romp of an episode, Tristan, Julia and DeVaris flow from his experience in tech mentorship, into the nuts and bolts of Change Data Capture (CDC), and how streaming data infrastructure can help data teams provide better end user experiences.

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.

David is Sr. Director of Data at Lyst, and as leader of their analytics + data science teams he has followed the evolution of data roles closely over the past decade.

David spends a lot of time thinking about career progression + data team structure, and in this conversation with Tristan + Julia they dive into the classic individual contributor vs manager conundrum, migrating between warehouses, and reactive vs proactive data workflows.

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.

Julien has a unique history of building open frameworks that make data platforms interoperable. He's contributed in various ways to Apache Arrow, Apache Iceberg, Apache Parquet, and Marquez, and is currently leading OpenLineage, an open framework for data lineage collection and analysis.

In this episode, Tristan & Julia dive into how open source projects grow to become standards, and why data lineage in particular is in need of an open standard.

They also cover into some of the compelling use cases for this data lineage metadata, and where you might be able to deploy it in your 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.

Benn is Chief Analytics Officer and a Co-founder at Mode Analytics, but you may know him from his Substack newsletter (benn.substack.com), where each Friday he dives into a semi-controversial topic (recent examples: "Is BI Dead?" and "BI is Dead").

In this episode, Benn, Tristan & Julia finally hash out some of these debates IRL: what *is* the modern data stack, why is the metrics layer important, and what's the point of all of this?

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.

Seth Rosen has broken data Twitter many times, and in his early-fatherhood sleep deprivation developed a wonderful Twitter persona as the battle-tested data analyst.

IRL though Seth is a serious data practitioner, and as Founder at the data consultancy HashPath has helped dozens of companies get into the modern data stack + build public-facing data apps. Now, as the founder of TopCoat, he's empowering analysts to build + publish those same public-facing data apps.

In this episode, Tristan, Julia & Seth graciously dive into spicy debates around data mesh + "dashboard factories", and explore a future where data analysts become full-stack application developers.

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.