Building The Materialize Engine For Interacti...

Summary In this episode of the Data Engineering Podcast, Lucas Thelosen and Drew Gilson, co-founders of Gravity, discuss their vision for agentic analytics in the enterprise, enabled by semantic layers and broader context engineering. They share their journey from Looker and Goog ...  Show more

Summary In this episode of the Data Engineering Podcast, Jamie Knowles (Product Director) and Ryan Hirsch (Product Marketing Manager) discuss the importance of enterprise data modeling with ER/Studio. They highlight how clear, shared semantic models are a foundational discipline ...  Show more

Modern networked applications generate a lot of data, and every business wants to make the most of that data. Most of the time, that means moving production data through some transformation process to get it ready for the analytics process. But what if you could have in-app an ...

Algorithms & Data Structures are critical to Backend Engineering however it really depends on what kind of application and infrastructure you are building. In this video I want to go through the following   1 Backend Engineers are two types - Integrating Existing ...

In this episode I speak about data transformation frameworks available for the data scientist who writes Python code. The usual suspect is clearly Pandas, as the most widely used library and de-facto standard. However when data volumes increase and distributed algorithms are ...

This is one episode where passion for math, statistics and computers are merged. I have a very interesting conversation with Ravin,  data scientist at Google where he uses data to inform decisions.

He has previously worked at Sweetgreen, designing systems that would b ...