Tag Archives: data divestiture

Creating Subsets Of Test Data For Database Applications Addresses Key Issues

Test data sets need to be created to validate or confirm specific use cases during testing and development phases for packaged or custom database applications.   Most companies use full copies of production data to seed test data sets.  Using live, up to date data is preferable by Quality Assurance teams to increase confidence in the testing results. Two key issues with using full live data sets are increasing costs as well as introducing security risks.

Full Copies of Production Data Sets Increase Cost

As the data volumes grow, so does each copy of the data used in each test environment, increasing the cost of infrastructure required to store and maintain performance with larger data volumes and increasing the time it takes to complete testing cycles. According to the Enterprise Strategy Group, the number of secondary copies of production data sets required for development, testing and training is four (at a minimum).  Multiply the size of the production data sets for each copy to get the total cost of ownership.  With larger data sets, queries and reports take longer to complete.  Many times, functional tests only require a small segment of data to validate a test.  Subsets of test data would be adequate for most testing scenarios. (more…)

FacebookTwitterLinkedInEmailPrintShare
Posted in Application ILM, Business Impact / Benefits, Data Integration, Data masking, Data Privacy, Operational Efficiency | Tagged , , , , , , | 3 Comments

Using Data Subset For Divestiture

As the market continues to consolidate and companies sell off assets, not only are the physical assets separated and sold, so are the digital assets – or liabilities. John Schmidt covered it in one of his recent blogs.

When the information to be separated and sold resides in a database, you need to understand the data model and determine what master data, or reference data, and transactions belong to the new company.  In the case of separating master data this may involve understanding the relationships between multiple systems to make sure that when the data is moved into the new company, it maintains context, is accurate and complete.  With transactional data, you need to know the tables and rows that comprise a complete transaction so that when data is moved, no orphaned rows are left behind.

(more…)

FacebookTwitterLinkedInEmailPrintShare
Posted in Application ILM, Data Integration, Data Migration, Enterprise Data Management, Master Data Management, Mergers and Acquisitions, Operational Efficiency | Tagged , , , , , | Leave a comment