Bitwise consultants have designed a special set of automated tools and utilities to test the graph and provide defect-free delivery, while ensuring repeatable and accurate testing of defined scenarios. This meets end-to-end testing requirements and ensures coverage of all test scenarios, whether Developer tested or Tester (QA) tested situations.
No matter if you plan to follow “white box” testing (i.e., Developer testing) or “black box” testing (Tester [QA] testing), Bitwise has special testing tools and utilities for each approach, which maximizes the potential value, reducing coding errors and helps to define standards to ensure code quality.
- Comparison Graph tool/utility to help validate code behavior by comparing data before and after code changes
- Build reusable unit test cases that require very little changes as per change in specifications and ETL transformations
- Validation extension tools to validate and report syntactical error in the graph
- Automate basic test cases using same mapping data provided to ETL Developer
- Automate the data comparison to ensure that results are as expected over multiple regression test runs
- Generate logical data (e.g., logical set of First Name, Last Name, and Address to generate customer data)
- Batch test cases for related ETLs into test suite
- For every change in ETL, schedule re-execution of suite of test cases
- Publish test results in easy-to-read dashboards
- Integrate with quality tracking tools like HPQC or JIRA
Realized Efficiency Gains
The Bitwise testing methodologies will lead to significant efficiency gains, as the documented client experiences listed below demonstrate:
- Achieved 30% reduction in test data creation effort
- Achieved 35% reduction of post-production implementation fixes needed as a result of running similar ETL batch streams
- Benefits of up to 30% reduced time to test and go to production, as seen with automated execution of test suites
You can download the detailed PDF version of this use case here.