A Primer on Data Architecture

For Data Engineers

This is one of those tricky topics that doesn’t seem to get much conversation in the data world these days. Too many other fun things are going on, dbt, polars, Rust taking over, just to name a few.

I have a feeling most people think of Architecture like a glorified lego game. You have a bag of tools, Airflow, Snowflake, Databricks, whatever, and you simply pick a few that you like and move on with life.

Sometimes this approach works out, and sometimes it doesn’t. Probably says more about the organization or team that approaches Data architecture like this.

What is Data Architecture, and why does it matter?