Time Keeps on Slippin…Automating Report Date Filters through Metadata

Presentation Summary

Darin Mattke, University of Texas Austin

Situation: Data is loaded at variable release dates (12th Class day; after ‘close’ of month). It is available in our reporting environment to a select set of users and data stewards for data validation prior to production release. Issue: Data is in a single location, i.e. we do not utilize a test database environment for data validation prior to loading to production. The difference between data validation and production reports is determined by date filter criteria hard-coded in each report. Process: Reports and cubes are automatically refreshed using a system of scripts and utilities. However, definitions of data validation and production reports are manually and individually updated. This opens the possibility of human error in a number of instances and is time consuming to re-code reports in addition to the routine data validation and verification process. Solution: “Chronos!” A home-grown initiative to automate the process of placing data into various states of production. A dynamic date dimension is used for a table-driven filter system that will identify valid date ranges and various readiness states of data. This reduces report coding time and the error-prone process. See how this is done and discuss alternative options!