The Analytics Engineering Podcast

ClickHouse, the lightning-fast open source OLAP database, was initially released in 2016 as an open source project out of Yandex, the Russian search giant. In 2021, Aaron Katz helped form a group to spin it out of Yandex as an independent company, dedicated to the development + commercialization of the open source project. In this conversation with Tristan and Julia, Aaron gets into why he believes open source, independent software companies are the future. And of course, this conversation wouldn't be complete without a riff on the classic "one database to rule all workloads" thread. 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.

Justin Borgman is the co-founder, Chairman and CEO of Starburst, and has almost a decade spent in senior executive roles building new businesses in the data warehousing and analytics space.  In this conversation with Tristan and Julia, Justin dives into the nuts and bolts of Trino, the open source distributed query engine, and explores how teams are adopting a data mesh architecture without making a mess.  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.

Amit Prakash is Co-founder and CTO at ThoughtSpot. He has a deep background in search, having previously led the AdSense engineering team at Google and served on the early Bing team at Microsoft. In this conversation with Tristan and Julia, Amit gets real about the promise of AI in data: which applications are being widely used today, and which are still a few years out? 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.

Most recently leading a data engineering team at Perpay, Sarah has built and managed data platforms end to end by working closely with internal engineering, product, and operational teams. She recently left her role to pursue a wide variety of endeavors, including writing on her Substack (https://sarahsnewsletter.substack.com/). In this conversation with Tristan and Julia, Sarah dives into how configuration-as-code can automate away data work, why you might want to consider adding a data lake to your architecture, and how those looking to build a self-serve data culture can look to self-serve frozen yogurt shops for inspiration. 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 a PhD candidate at MIT, Kevin (and friends) published Sherlock, a data type detection engine (a surprisingly bedeviling problem) for data cleaning + data discovery. Now as co-founder and CEO of Metaplane, a data observability startup, Kevin applies these same automated data discovery methods to help data teams keep their data healthy. In this conversation with Tristan & Julia, Kevin wins the coveted award for “most crystal-clear explanations of complex technical concepts through physics analogy.”   For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

A debate has erupted on data Twitter and data Substack - should the modern data stack remain unbundled, or should it consolidate? In this conversation, Benn Stancil (Mode), David Jayatillake (Avora) and our host Tristan Handy try to make some sense of this debate, and play with various future scenarios for the modern data stack.  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.

Will the dream of a mythical database to handle all workloads (transactional + analytical) ever become a reality, or does it violate the laws of physics? This question sparked a hearty debate internally at dbt Labs, and Jon "Natty" Natkins joins Julia here to continue the conversation. Natty knows databases, and this episode will take you on a historical romp through the rise and fall of Hadoop, the transition to cloud data warehouses, and what's waiting for us next in database-land. 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.

Ashley is a Principal Analytics Engineer at Hubspot, and has helped lead their implementation of dbt. Ashley makes unique connections in her writing and work. On her Substack, "syntax error at or near ❤️," Ashley might be found comparing growing companies to butterflies, or going deep on how to accommodate sensitive people in the workplace. In this conversation with Tristan & Julia, Ashley dives into the nuts and bolts of her trajectory pushing data innovation forward at Hubspot. 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 very special episode, we’ll be turning the spotlight on co-host Tristan Handy, the CEO & Co-founder of dbt Labs. In this AMA with Julia, you’ll get to know more about Tristan as a human, as a writer, and as the CEO of dbt Labs helping to push the analytics engineering practice forward.  For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. 

Your company has one definition for revenue across the organization, one definition of the customer, and one definition of sign-up. For people whose jobs are so defined by ensuring we’re aligned, we can’t seem to standardize on one definition for the Data Scientist. In this talk, Emilie Schario (Data Strategist-in-Residence at Amplify Partners and longtime dbt community member) proposes we lobby against the title Data Scientist, instead choosing some variation of the Core Four Data Roles: Data Analyst, Analytics Engineer, Data Engineer, and Machine Learning Engineer. 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.