Benefits of Data Subsetting using Test Data Automation

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Test Data Automation offers data subsetting, a high-speed test data management utility for copying referentially intact slices of data.

Testing with small subsets of data is useful for a number of reasons. Data Subsetting from Test Data Automation enables:

  1. Parallel testing and development. Multiple testers and developers can work in parallel from the same data, using isolated subsets. This helps avoid delays caused by cross-team constraints and avoids the further frustration of test data being edited, moved or deleted by another tester or developer.
  2. Shorter test run times. Test run time is shortened, using smaller but representative sets of data that are quicker to run and produce less cumbersome results.
  3. Faster, less costly masking. Masking is also quicker and more affordable, masking a smaller, representative data set instead of full-sized copies.
  4. More efficient data extracts. Slow and cumbersome extracts of large data sets are avoided, instead using a high-speed utility to extract only as much data as is needed.
  5. Quicker testing and development. Test and development teams spend less time searching for data, working instead from data sets just big enough to fulfil their exact needs.
  6. A greater understanding of your data. Subsetting further enables easier data exploration, running exploratory subsets instead of experimenting with complex data joins.