Track: Specialized Application Test Environments
When a company builds a data warehouse and creates reports designed for business analysis, it’s important that the data on those reports is accurate. Critical business decisions are made on the basis of the data on reports – but how do you know the data is accurate?
Testing for data accuracy is different from functional testing and other types of testing such as performance or security testing. The business rules around data become boundary conditions to consider. Historical production data often reveal discrepancies in business rules raising ongoing concerns about how bad data got into production in the first place.
Data testing on business intelligence projects highlights existing issues and forces decisions to be made about data quality. The volume of data to test is frequently so large that testing all the data is not possible, so deciding the test data set becomes a considerable topic and is often one of the most strategic decisions in BI testing.
Stored procedures, triggers, and custom ETL transactions need to be tested but frequently testers don’t have these types of experiences on their resume which makes building a testing team a challenge for most test managers. What needs to be tested? How do you test OLAP cubes and ETL jobs? How do you hire and prepare staff for intense data testing?
This session takes a look at the unique testing challenges of data quality in the business intelligence/data warehouse arena.
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Karen N. Johnson – Founder, Software Test Management, Inc.
Karen N. Johnson is an independent software test consultant. She is a frequent speaker at conferences. Karen is a contributing author to the book, Beautiful Testing released by O’Reilly publishers. She is the co-founder of the WREST workshop, more information on WREST can be found at: http://www.wrestworkshop.com/Home.html. She has published numerous articles and blogs about her experiences with software testing. You can visit her website at: http://www.karennjohnson.com