Let's kick this off! First topic: BI! There are many blog posts these days that BI is dead. Do you agree? Coincidentally to us creating this channel today, Maxime Beauchemin (considered by many as a "father" of data engineering) gave s I've seen about the topic. As a person who is quite obsessed with naming things correctly (without using BS marketing terms), I love how Maxime disambiguates many terms used in the data industry, including: • why BI is a loaded term -- data consumption layer is much more appropriate these days • why headless BI is a complete BS term introduced by marketing folks. Maxime claims that while managing assets as code may have its merits, the industry needs a more pragmatic approach with tooling that can consolidate the everything-as-code world with the GUI world by building more user-friendly interfaces and tools that consolidate both in a bidirectional manner • why Gartner’s BI magic quadrant is also pretty much BS, especially these days when the Modern Data Stack allows you to pick and choose your stack, • why the semantic layer doesn’t make much sense these days and why has it failed to deliver on a promise of self-service -- instead, a more sensible approach is shifting this more toward the transformation layer • he also covered many trends in the data "space" including data apps - bringing the visualizations out of the BI layer into the tools we use every day. I highly recommend watching this talk!

father of data engineering - I’m intrigued …

you can check this blog post he wrote in Jan 2017 that explains it a bit more

This 💪🏽💪🏽💪🏽🥳

“data engineers should be constantly looking to automate their workloads and building abstraction that allow them to climb the complexity ladder. While the nature of the workflows that can be automated differs depending on the environment, the need to automate them is common across the board.”