Databricks is fantastic, but there is a small issue with how people use it. The problem is that Databricks is all things to all people. Data scientists and data analysts use Databricks to explore their data and write cool things. ML engineers use it to get their models to execute somewhere. Meanwhile, the cool kids (data engineers obviously) use it to run their ETL code. Some use cases favour instant access to “all the datas”, some favour rigorous engineering discipline so when we look at Databricks it is a case of one size does not fit all.