ETL-Testing-Types-and-Best-Practices. ETL testing processIt is vital that you define the right ETL testing process before beginning the testing procedure. You should take an acceptance from every one of the partners and guarantee that the right system is chosen to perform ETL testing.

These ETL testing concepts should be notable to the testing team and they should know about the means associated with the testing procedure.

All the IT organizations today, exceedingly rely upon data flow due to a lot of data is made accessible for access and one can get everything which is required.

Also, this is the place the idea of ETL and ETL Testing comes into the image. Fundamentally, ETL is abbreviated as Extraction, Transformation, and Loading. Generally, ETL Testing process is performed utilizing SQL scripting or utilizing spreadsheets which might be a time-consuming and error-prone methodology.

 

ETL testing types can be arranged into the accompanying classifications as per the testing procedure that is been followed:

Production Validation Testing:

It is additionally called product reconciliation or table balancing. It is performed on information previously or while being moved into the production system in the right order.

Source To Target Testing:

This kind of ETL Testing approach is performed to approve the data value after data change.

Application Upgrade:

It is utilized to check whether the information is removed from an older application or new application or store.

Data Transformation Testing:

Different SQL questions are required to be kept running for every single line to confirm information change models.

Data Completeness Testing:

This sort of ETL process is performed to confirm if the expected data is loaded at the appropriate goal according to the predefined principles.

To test an ETL data warehouse or a BI application, one needs a data-driven methodology. ETL Testing best practices help to limit the expense and time to perform the ETL testing process. It enhances the quality of data to be loaded to the objective system which produces high-quality dashboards and reports for end-clients.

We have recorded here a couple of ETL testing methodology best practices that can be followed for ETL Testing:

  • Ensure information is transformed effectively
  • With no information loss and truncation projected data should be loaded into the data warehouse testing.
  • Guarantee that ETL application properly rejects and replaces with default values and reports invalid information
  • Need to guarantee that the information loaded in the data warehouse ETL testing inside endorsed and anticipated that time frames would affirm scalability and performance
  • All techniques should have suitable unit tests paying little respect to visibility
  • To measure their viability all unit tests should utilize proper coverage procedures
  • Make progress toward one assertion per test case
  • Make unit tests that target exceptions

ETL testing automation is one of the oldest types of data integration, and it is as yet applicable for modern enterprises hoping to end up data-driven. In any case, the ETL procedure has moved with the rise of data pipelines and cloud computing offered as-a-benefit. Notwithstanding the technique, your enterprise utilizes ETL data into an objective data warehouse or other analytical stores; it’s basic to completely test your ETL to guarantee exactness, consistency, and speed.

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