Data Validation Testing

November 16, 2015

Nowadays, a fast-growing client demand leads to huge amounts of data that each competitive product should deal with correctly and effectively. Every day you need more and more terabytes to store that all, every day you need to add something completely new to your system. This process is cruel and never stops. To stay on a stage you need to have a well-tuned team of professionals working effectively to satisfy all the market whims and Data Validation is an important part of things to take care here.

Data Validation Testing allows you to make sure that the Data you deal with is correct and complete; that your Data and Database can go successfully through any needed transformations without loss; that your Database can dwell with specific and incorrect data in a proper way and finally, that you have all the Data you expect to see in the front end of your system been represented correctly corresponding to the input.

There is a number of testing techniques and approaches to help you accomplish these tasks above:

  • Data Accuracy Testing – makes sure that data is correct;
  • Data Completeness Testing – makes sure that data is complete;
  • Data Transformation Testing – makes sure that data goes successfully through transformations;
  • Data Quality Testing – makes sure that bad data is handled well;
  • Database Comparison Testing – compares the source and target DB despite the fact their structure and volume differ;
  • Data Comparison Testing – compares data between different points of data flow;
  • End-To-End Testing – final system testing that makes sure that in the end point we have correct data according to what we put into start point of the data flow;
  • Data Warehouse Testing – makes sure that data goes successfully through all points of the system that uses data warehouse.

Data Warehouse Testing is a separate specific and complicated testing task that includes the number of subsequent test activities:

  • Test Data Acquisition – makes sure all data from all sources is acquired;
  • ETL Testing – makes sure that all goes well in extract, transform and load processes;
  • Data Accuracy Testing;
  • Data Transformation Testing;
  • Data Load – makes sure data is loaded within expected length of time;
  • OLAP Testing – makes sure that the data is mapped from the data warehouse and designed correctly to the OLAP cubes;
  • Report Testing – the final destination of the data is usually a report where data should be the same as expected according to the input.

Ok, what I’m saying, you can’t test it yourself or with one suppa-duppa-cool-test-specialist. You need a good QA team to take care of all this stuff and specialists who are not afraid of huge amount of data testing.

Yulia has been with Core Value as a QA Manager for over 4 years.  Yulia enjoys physical training, travelling, and playing the piano.


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