The Analytics Engineering Podcast
The Analytics Engineering Podcast features in-depth conversations with practitioners and builders who are leading the shift in how data work is done. Hosted by Tristan Handy, founder and CEO of dbt Labs, each episode covers topics such as data transformation, AI in analytics, data architecture, and working with data at scale. Guests include data engineers, analytics engineers, and technical leaders in the agentic era. Full show notes and transcripts are available at roundup.getdbt.com.
Episodes
The context engineering playbook (Claire Gouze)
nao co-founder and CEO Claire Gouze shares a practical playbook for building a context layer your agents can actually rely on. For full show notes and to read the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.
DuckDB's agent moment (Jordan Tigani)
Jordan Tigani helped build BigQuery, then left to bet that most data isn't big. Three years on, agents are proving him right. The MotherDuck CEO joins Tristan Handy on why local-first databases fit the agent era, and what an "agent swarm for data management" looks like. For full show notes and to read the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering
The Iceberg ecosystem today (w/ Anders Swanson)
Tristan sits down with Anders Swanson, a developer experience advocate at dbt Labs, to talk about the state of the Apache Iceberg ecosystem. They unpack the "open standards" shift, define the core building blocks (query engines, object stores, catalogs), and dig into why external catalogs have become a fourth namespace tier across platforms. Anders outlines a pragmatic, phased adoption model for I
Apache Iceberg and the catalog layer (w/ Russell Spitzer)
Tristan talks with Russell Spitzer, a PMC member of Apache Iceberg and principal engineer at Snowflake, about the evolution of open table formats and the catalog layer. They dig into identity and access at the catalog layer and why consensus‑driven standards make interoperability possible. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https:
AI and the data lake (w/ Lauren Anderson)
Tristan talks with Lauren Anderson, Senior Director for Okta's Enterprise Data Platform. Lauren shares how identity sits at the center of two seismic shifts in data—AI agents and the open data lake—and why central governance and a shared semantic layer are critical. Lauren lays out how analytics engineers and data engineers should divide responsibilities as agents begin to write a growing share of
Inside Snowflake's AI roadmap (w/ Chris Child)
Snowflake VP of Product Management Chris Child joins Tristan Handy to unpack Snowflake's AI roadmap and what it means for data teams. They discuss the evolution from Snowpark to Cortex and Snowflake Intelligence, how to govern agents with row- and column-level controls, and why Snowflake is investing in Apache Iceberg and the Open Semantic Interchange initiative (dbt Labs recently open sourced M
Building a multimodal lakehouse for AI (w/ Chang She)
In this episode, Tristan Handy sits down with Chang She — a co-creator of Pandas and now CEO of LanceDB — to explore the convergence of analytics and AI engineering. The team at LanceDB is rebuilding the data lake from the ground up with AI as a first principle, starting with a new AI-native file format called Lance. Tristan traces Chang's journey as one of the original contributors to the pandas
Agentic coding in analytics engineering (w/ Mikkel Dengsøe)
Tristan talks with Mikkel Dengsøe, co-founder at SYNQ, to break down what agentic coding looks like in analytics engineering. Mikkel walks through a hands-on project using Cursor, the dbt MCP server, Omni's AI assistant, and Snowflake. They cover where agents shine (staging, unit tests, lineage-aware checks), where they're risky (BI chat for non-experts), and how observability is shifting from das
Under the hood of Apache Iceberg (w/ Christian Thiel)
Tristan digs deep into the world of Apache Iceberg. There's a lot happening beneath the surface: multiple catalog interfaces, evolving REST specs, and competing implementations across open source, proprietary, and academic contexts. Christian Thiel, co-founder of Lakekeeper, one of the most widely used Iceberg catalogs, joins to walk through the state of the Iceberg ecosystem. For full show notes
The pragmatic guide to AI agents in the enterprise (w/ Sean Falconer)
What does it mean to be agentic? Is there a spectrum of agency? In this episode of The Analytics Engineering Podcast, Tristan Handy talks to Sean Falconer, senior director of AI strategy at Confluent, about AI agents. They discuss what truly makes software "agentic," where agents are successfully being deployed, and how to conceptualize and build agents within enterprise infrastructure. Sean sha
How Amazon S3 works (w/ Andy Warfield)
In this season of the Analytics Engineering podcast, Tristan is deep into the world of developer tools and databases. If you're following us here, you've almost definitely used Amazon S3 it and its Blob Storage siblings. They form the foundation for nearly all data work in the cloud. In many ways, it was the innovations that happened inside of S3 that have unlocked all of the progress in cloud dat
From Docker to Dagger (w/ Solomon Hykes)
In this season of the Analytics Engineering podcast, Tristan is digging deep into the world of developer tools and databases. There are few more widely used developer tools than Docker. From its launch back in 2013, Docker has completely changed how developers ship applications. In this episode, Tristan talks to Solomon Hykes, the founder and creator of Docker. They trace Docker's rise from start
The history and future of the data ecosystem (w/ Lonne Jaffe)
In this decades-spanning episode, Tristan Handy sits down with Lonne Jaffe, Managing Director at Insight Partners and former CEO of Syncsort (now Precisely), to trace the history of the data ecosystem—from its mainframe origins to its AI-infused future. Lonne reflects on the evolution of ETL, the unexpected staying power of legacy tech, and why AI may finally erode the switching costs that have lo
Everything terminals (w/ Zach Lloyd)
In this episode, Tristan talks to Zach Lloyd, founder of Warp—a terminal built for the modern era, including for AI agents. They explore the history of terminals, differences between terminals and shells, and what the future might look like. In a world driven by generative AI, the terminal could once again be the control center of computer usage. For full show notes and to read 6+ years of back is
Why compilers matter (w/ Lukas Schulte)
In this episode, Tristan Handy and Lukas Schulte, co-founder of SDF Labs and now part of dbt Labs, dive deep into the world of compilers—what they are, how they work, and what they mean for the data ecosystem. SDF, recently acquired by dbt Labs, builds a world-class SQL compiler aimed at abstracting away the complexity of warehouse-specific SQL. Join Tristan and members of the SDF team at the dbt
The evolution of databases (w/ Wolfram Schulte)
In the first episode of our new season on developer experience, the cofounder and CTO of SDF Labs, now a part of dbt Labs, discusses databases, compilers, and dev tools. Wolfram spent close to two decades in Microsoft Research and several years at Meta building their data platform. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundu
Building a data team from the beginning (w/ Daniel Avancini)
Daniel Avancini is the chief data officer and co-founder of Indicium—a fast-growing data consultancy started in Brazil. There are a lot of data consultancies around the world, and a lot of them do great work. What has been so fascinating about Indicium's journey is their HR model. Rather than primarily hiring experienced professionals, they decided to go hard on training. They built a talent pipe
Data engineering at Snowflake (w/ Rahul Jain)
A look inside at the data work happening at a company making some of the most advanced technologies in the industry. Rahul Jain, data engineering manager at Snowflake, joins Tristan to discuss Iceberg, streaming, and all things Snowflake. 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 Pod
The intersection of UI, exploratory data analysis, and SQL (w/ Hamilton Ulmer)
Hamilton Ulmer is working at the intersection of UI, Exploratory Data Analysis, and SQL at MotherDuck, and he's built a long career in EDA. Hamilton and Tristan dive deep into the history of exploratory data analysis. Even if you spend most of your time below the frontend layer of the stack, it is important to understand the trends in both the practice of data visualization and the technologies t
Making data movement as reliable as electricity (w/ Taylor Brown)
Fivetran recently passed $300 million ARR and has over 7,000 customers globally. Taylor Brown, the cofounder and COO of Fivetran, joins the show to talk about Fivetran's moat, the impact of AI on the data ingestion space, and open table formats and catalogs. 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 Analy
Data as an assembly line (w/ Cedric Chin)
Cedric Chin runs Commoncog—a publication about accelerating business expertise. He joins Tristan to talk about the analytics development lifecycle, how organizations value (or misvalue) data, and why "data teams are not some IT helpdesk to be ignored." 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
The data jobs to be done (w/ Erik Bernhardsson)
Erik Bernhardsson, the CEO and co-founder of Modal Labs, joins Tristan to talk about Gen AI, the lack of GPUs, the future of cloud computing, and egress fees. They also discuss whether the job title of data engineer is something we should want more or less of in the future. Erik's not afraid of a spicy take, so this is a fun one. For full show notes and to read 6+ years of back issues of the podc
Coalesce 2024 edition: What's next for data teams? (w/ Scott Breitenother)
Show description: Scott Breitenother, founder of data consultancy Brooklyn Data Co., joins Tristan at Coalesce 2024 in Las Vegas to discuss the early days of dbt, the evolution of data teams, and what's next for the dbt community. 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 s
The current state of the AI ecosystem (w/ Julia Schottenstein)
Former co-host Julia Schottenstein returns to the show to go deep into the world of LLMs. Julia joined LangChain as an early employee, in Tristan's words, to "Basically solve all of the problems that aren't specifically in product and engineering." LangChain has become one of, if not the primary frameworks for developing applications using large language models. There are over a million developers
Creating value from GenAI in the enterprise (w/ Nisha Paliwal)
Nisha Paliwal, who leads enterprise data tech at Capital One, joins Tristan to discuss building a strong data culture for in the world of AI. She is the co-author of the book Secrets of AI Value Creation. 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.
Developer productivity on GitHub Copilot (w/ Eirini Kalliamvakou)
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 dev
The rapid experimentation of AI agents (w/ Yohei Nakajima)
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 discusse
Funnel analytics and AI models for event sequences (w/ Misha Panko)
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 eve
From Moneyball to Gen AI
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 featur
Being Pro-Human in the AI Era
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 cycl
The 2024 Machine Learning, AI & Data Landscape (w/ Matt Turck)
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 bee
How the Media Covers Gen AI (w/ Matthew Lynley, Supervised)
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
AI's Impact in the World of Structured Data Analytics (w/ Juan Sequeda, data.world)
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
The End of the Modern Data Stack (w/ Benn Stancil, Mode)
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.get
Data Mesh Architecture at Large Enterprises (w/ Moritz Heimpel and Ben Flusberg)
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
Let's Talk About Data Vault (w/ Brandon Taylor and Michael Olschimke)
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
Navigating AI Complexity (w/ Jonathan Frankle)
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 pot
Career Growth in Data Roles (w/ Hubspot's Kasey Mazza at Coalesce 2023)
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 sh
Operationalizing Your Warehouse, Streaming Analytics, and Cereal (W/ Arjun Narayan of Materialize and Nathan Bean of General Mills)
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 str
Roche's Data Transformation Journey (w/ Yannick Misteli)
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
The State of Databases Today (w/ Andy Pavlo)
Andy Pavlo is a professor of databaseology (he says it's a made-up word) at Carnegie Mellon and currently on leave to build his own company—OtterTune, which uses AI to figure out the settings to get the best performance out of databases. He is one of the preeminent minds on databases and a die-hard relational database maximalist. We talk about the state of databases today, why there are so many sp
Bring Your Own Data to LLMs (W/ Jerry Liu of LlamaIndex)
Jerry Liu is the CEO and co-founder of LlamaIndex. LlamaIndex is an open-source framework that helps people prep their data for use with large language models in a process called retrieval augmented generation. LLMs are great decision engines, but in order for them to be useful for organizations, they need additional knowledge and context, and Jerry discusses how companies are bringing their data
Ramp's $8 Billion Data Strategy (W/ Ian Macomber and Ryan Delgado)
Ian Macomber, head of analytics engineering and data science at Ramp and formerly the VP of analytics and data engineering at Drizly, and Ryan Delgado, a staff software engineer at Ramp, have played pivotal roles in establishing Ramp's data team from the ground up and are spearheading the development of their comprehensive roadmap. In this conversation with Tristan and Julia, Ian and Ryan share in
dbt Labs on dbt (w/ Daniel Le)
Daniel Le is the CFO at dbt Labs where he has built multiple teams. He is also the former head of FP&A and operations at Zoom, and he helped scale FP&A as the former finance director at Okta. In this conversation with Julia, Daniel shares his view as CFO on the challenges SaaS companies face and the importance of finance teams creating a holistic view of their business. Daniel gives advice to dat
The Arc of Data Innovation (w/ Bob Muglia, former CEO of Snowflake)
Bob Muglia likely needs no introduction. The former CEO of Snowflake led the company during its early, transformational years after a long career at Microsoft and Juniper. Bob recently released the book The Datapreneurs about the arc of innovation in the data industry, starting with the first relational databases all the way to the present craze of LLMs and beyond. In this conversation with Trist
It's 2023, and Privacy Is Now Fun! (w/ Ian Coe of Tonic.ai + Abhishek Bhowmick of Samooha)
Advances in ML have transformed data privacy from a regulatory necessity into an opportunity to improve the work of data people. Synthetic data for modeling + testing is one example of a hard thing that's now easy - and in this conversation with Tristan and Julia, Ian + Abhishek cover many other ways that privacy can actually be a skill that propels your work forward, rather than a mere legal best
Julia, Pedram Navid + Taylor Murphy Recap Data Council
Julia just got back from Data Council in Austin, a conference organized by Pete Sonderling, where lots of startups share what they're building, data practitioners go to learn in hands-on workshops, and of course investors go to spot the next big trend. In this episode, Taylor Murphy (Head of Product & Data at Meltano) + Pedram Navid (Founder, West Marin Data) join Julia to recap the conference and
Cloud Warehouse Cost Optimization (w/ Niall Woodward + Brad Culberson)
Brad Culberson is a Principal Architect in the Field CTO's office at Snowflake. Niall Woodward is a co-founder of SELECT, a startup providing optimization and spend management software for Snowflake customers. In this conversation with Tristan and Julia, Brad and Niall discuss all things cost optimization: cloud vs on-prem, measuring ROI, and tactical ways to get more out of your budget. For full
dbt Labs + Transform Join Forces on Metrics (w/ Nick Handel + Drew Banin)
Nick Handel, as co-founder at Transform, helped develop the popular open source metrics framework MetricFlow. Drew Banin, a co-founder at dbt Labs, helped build the initial version of the dbt Semantic Layer, which launched last year. Transform was acquired in February by dbt Labs, and in this conversation with Tristan, they talk through their collective plans for the future of the dbt Semantic L
What Can Generative AI Do for Data People? (W/ Sarah Nagy + Chris Aberger)
Sarah and Chris are both at the forefront of bringing the promise of gen AI to our actual work as data people—which is a unique challenge! Precise truth is critical for business questions in a way that it's not for a consumer search query. Sarah Nagy is the CEO of Seek AI, a startup that aims to use natural language processing to change how professionals work with data. Chris Aberger currently le
3rd Party Data, Demystified
Auren Hoffman currently serves as the CEO and Chief Historian at SafeGraph, a data-as-a-service company he founded, which provides primarily location data. In this conversation with Tristan and Julia, Auren shares how truly few companies are making use of 3rd-party datasets today, how opening up more datasets to public research could help us solve big problems, and a fun fact about Abraham Lincol
A Romp Through Database History (w/ Postgres co-creator Mike Stonebraker + Andy Palmer)
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
What Does Apache Arrow Unlock for Analytics? (w/ Wes McKinney)
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? T
Minimum Viable Experimentation
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 sam
The Data Generalist's Vision Quest (LIVE w/ Stephen Bailey)
The first LIVE IRL episode! Stephen Bailey, data engineer at Whatnot and writer of an incredibly entertaining data substack, joins Tristan for a follow-up conversation to Stephen's Coalesce talk, "Excel at nothing: how to be an effective generalist." You can read Stephen's writing at https://stkbailey.substack.com/. For full show notes and to read 6+ years of back issues of the podcast's compani
Why You'll Need Data Contracts (w/ Chad Sanderson + Prukalpa)
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 dat
How Does Data Drive Growth in Practice? (w/ Abhi Sivasailam)
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 y
Katie Bauer: Data Scientists Are Not Pizza
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
Data Activation Everywhere (w/ Julie Beynon of Clearbit)
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
The Personal Data Warehouse (w/ Jordan Tigani of MotherDuck)
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
Making Sense of the Last 2 Years in Data
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
Building an Open Source Company (w/ Aaron Katz of ClickHouse)
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 believe
"To Move, or Not to Move" (Data). That is the Question.
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
What's The Role Of AI in BI?
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
Automating Away Your Work w/ Configuration-as-Code (w/ Sarah Krasnik)
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 con
The Hard Problems™️ of Data Observability w/ Kevin Hu of Metaplane
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 co
The Bundling vs Unbundling Debate w/ Tristan, Benn Stancil and David Jayatillake
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 podca
One Database to Rule All Workloads? With Jon "Natty" Natkins of 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, t
Ashley Sherwood (AE @ Hubspot): Permissionless Innovation for Data Teams
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 i
Tristan in the Hot Seat
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 h
[COALESCE] Down With "Data Science" w/ Emilie Schario of Amplify Partners
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 a
[COALESCE] Peeking Into the Future of Data Analytics w/ Julia
How is the data landscape evolving, what trends should you pay attention to and which should you ignore? In this panel, Julia Schottenstein (our fearless co-host and dbt Labs product manager) catches up with Sarah Catanzaro, Jennifer Li and Astasia Myers to dive into the trends playing out in our work. Register to catch the rest of Coalesce, the Analytics Engineering Conference, at https://coalesc
[COALESCE] The Modern Data Experience w/ Benn Stancil of Mode
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.
[COALESCE] Data Analytics In A Snowflake World ft. Christian Kleinerman
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 Engineerin
[COALESCE] You Don't Need Another Database W/ Reynold Xin of Databricks and Drew Banin of 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 Conf
[COALESCE] How big is this wave? Ft. Martin Casado of a16z
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 ultimatel
[COALESCE] Scaling Knowledge > Scaling Bodies: Why dbt Labs is making the bet on a data literate organization (ft. Erica Louie of 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
DeVaris Brown: Bringing Streaming Data to Analysts
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
David Jayatillake: Should Great Data People Become Managers or Not?
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, a
Julien Le Dem: Why Data Lineage Matters
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 line
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