MarsTQM: Revolutionizing ETL Testing


How Is MarsTQM Different?

ETL Testing has come a long way from the early days of automation scripts as the norm rather than the exception. There are a lot of tools available, including homegrown and out-of-the-box SQL-based, that improve data quality and reduce testing time.

These tools hit all the KPIs of an ideal testing process for 80% of the scenarios where no transformations on data are required, but for the other 20% of scenarios with transformations that traditionally take up 80% of the testing time and the biggest causes of unidentified defects, there are still significant unaddressed challenges.

Missed test scenarios leading to unidentified defects:

  • Test scenario identification is still manual, and the more complex the transformation, the more skill a tester needs to identify all the scenarios.
  • Manual processes are always error-prone.

Data setup is not automated:

  • A significant amount of testing time is taken up by this process.
  • It’s very hard to keep the test data pristine when there is an overlap of source data being used across multiple project teams.
  • Test data errors produce false positives adding significant time to debugging processes.

SQL Coding is still required for execution and validation:

  • Even some simple transformations require significant SQL coding skills to generate the execution and validation query.
  • It’s always a challenge to hire and retain highly skilled testing resources.
  • Errors in SQL code lead to false positives and increase debugging time.

We have incorporated the skills of an analyst and a tester into our proprietary algorithms enabling MarsTQM to address these challenges and hit the KPIs of an ideal testing tool in 100% of the scenarios.

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