During the height of the business intelligence (BI) craze earlier in my career, I worked with an internal reporting team to expose data for extract, transform, and load (ETL) processes that leveraged data structures inspired by Ralph Kimball. It was a new and exciting time in my life to understand how to optimize data for reporting and analysis. Honestly, the schema looked upside down to me, based on my experience with transaction-driven designs.
In the end, there were many moving parts and even some dependencies for the existence of a flat file to make sure everything worked properly. The reports ran quickly, but one key factor always bothered me: I was always looking at yesterday’s data.