Building The Materialize Engine For Interacti...

Summary In this episode Jacob Leverich, cofounder and CTO of Observe, talks about applying lakehouse architectures to observability workloads. Jacob discusses Observe’s decision to leverage cloud-native warehousing and open table formats for scale and cost efficiency. He digs int ...  Show more

Summary In this episode Kostas Pardalis talks about Fenic - an open-source, PySpark-inspired dataframe engine designed to bring LLM-powered semantics into reliable data engineering workflows. Kostas shares why today’s data infrastructure assumptions (BI-first, expert-operated, CP ...  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 ...