I got tired of checking LinkedIn analytics in the UI. So I built a pipeline.
It runs every morning, lands the data in my own Databricks Lakehouse, and keeps accumulating history indefinitely. Something I own and can query freely. It also turns out to be a near-perfect project for learning how to build a proper Lakehouse: API ingestion, medallion architecture, and a dashboard, all in one manageable use case.
Part 1 of the series is live on my Blog thelakehousepath. We start with the foundation: setting up the project using Declarative Automation Bundles so that everything that follows slots in cleanly from the start.
Link to the Blog in the comments.
