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.

The products that make up the “modern data stack” have all grown to prominence over the past decade. In this heady time, so much has changed about how data work is done.

But some of the “rules of engagement” that defined the original modern data stack are starting to break down. As a result, big changes are coming for the data tooling ecosystem.

The end result? Better, more integrated tooling, used by more humans inside of every company, that actually understands the data that it is operating on.

This modern data stack—if we still want to call it that!—will be unrecognizable to its former self.

Check the slides here: https://docs.google.com/presentation/d/1G0c3w19AwBEWEzyd9vwTKK5zMvXR76-NPQn6x0xZoSg/view

Coalesce 2023 is coming! Register for free at https://coalesce.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.

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.