Columnstore compression is an impressive array of algorithms that can take large analytic tables and significantly reduce their storage footprint. In doing so, IO is also reduced, and query performance dramatically improved.
This article dives into one aspect of columnstore compression that tends to get buried in all of the hoopla surrounding how awesome columnstore indexes are: Vertipaq optimization. This is a critical component of the columnstore compression process, and understanding how it works can significantly improve the performance of analytic workloads while reducing the computing resources required for the underlying data.
Click through for the steps of the process.