What's Included
The Performance Reporting Problem
When satellite record load dates don’t match a requested point-in-time, the closest
record value of each satellite table on the requested date is used. But this can involve significant compute time. That’s exacerbated when requests add more satellites, records, users, or changes over time, resulting in a significant drain on the data vault’s compute resources.
Using PIT Tables to Solve the Performance Problem
Performance can degrade quickly depending on the quantity of satellite data and number of concurrent users analyzing data in the data vault. Architecting and implementing PIT tables—preset points-in-time—in advance anticipates user query needs to improve compute performance.
Optimizing Data PIT Storage Without Sacrificing Performance
Significantly reduce the data footprint a PIT requires by making some modifications to
the PIT’s DDL, slight code changes while creating the data in the PIT, and a small modification when querying the PIT. Smaller PIT record sizes will equate to faster performance while not losing any PIT functionality.
We’re proud to help organizations thrive, and we’d love to tell you more.
