Big data testing 101: the complete guide | Software Testing Company a1qa

Step 1. Pre-define big data testing strategy and its objectives

  • 23X more likely to attain new users
  • 6X more likely to reinforce customers’ loyalty
  • 19X more likely to increase revenue.

Step 2. Consider big data testing essentials

  • Data ingestion testing. To check that data is pulled into the system correctly, corresponds to the original values, and is extracted to the right location.
  • Data processing testing. To dodge any data discrepancy by asserting the business logic of ingested data and comparing output and input results. If used, test automation helps facilitate the verifying process and shorten the testing time.
  • Validating the outputs. To test further data transmitting to other more specific DBs that track customers’ feedback, internal processes, financial reports, etc., and check transformation logic as well as coinciding key value pairs.

Step 3. Perform mission-critical testing types

End-to-end testing

Integration testing

Architecture testing

Performance testing

Cybersecurity testing

Test automation

Summing up



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Software Testing & Quality Assurance Company. #QA #testing #mobile #security #performance #consulting #automation #telecom #ecommerce #banking #Agile #DevOps