Elements and Performance Criteria
- Validate assembled or obtained big data sample
- Establish a sampling strategy for big data testing and identify a representative sample for big data testing
- Assemble or obtain sample of raw big data according to legislative requirements and organisational policies and procedures
- Validate big data sample from various sources to ensure that big data is correct
- Validate big data sample process and business logic
- Align datasets to relevant parts of the organisation
- Implement data aggregation and segregation rules on a small set of sample data and datasets
- Consult with required personnel to clarify and resolve identified anomalies
- Conduct performance testing for data throughput, data processing and sub-component performance
- Validate output of captured big data sample and record results
- Design, formulate and select suitable test scenarios and test cases to validate output of big data sample
- Implement selected test scenarios and test cases with big data sample using common testing tools and according to organisational procedures
- Isolate sub-standard data and correct data acquisition paths as required
- Generate and store results of validation activity and associated supporting evidence according to organisational policies and procedures, and legislative requirements
- Optimise big data sample results and documentation
- Perform data cleansing on big data sample following testing according to industry practices and organisational procedures
- Collate validated output of testing, confirming absence of big data corruption in sample
- Recommend configuration optimisation changes based on performance testing results
- Communicate final sample results to required personnel