Unit of competency Outline

Date retreived
23/07/2026 6:51 AM AWST

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Test big data samples

Test big data samples

Unit of competency
National Code
BSBXBD402
State Code
OBO78
TGA Status
Current
DTWD Status
Approved
Current Release Number
1.00
Current Release Date
28/02/2020
View on TGA
State Implementation and Classification
Approved Date
14/05/2020
Field of Education
020305 - Systems Analysis And Design
Original Release Date
14/05/2020
Nominal Hours
35
Description
This unit describes the skills and knowledge required to test captured transactional and non-transactional big data samples prior to using them in the organisation. It involves assembling or obtaining raw big data, processing that big data, and testing it in a way that enables it to be used more broadly within the organisation.It applies to those who work in a broad range of industries using data analysis techniques in the management of their day-to-day work. No licensing, legislative or certification requirements apply to this unit at the time of publication.
Notes
Elements and Performance Criteria
1. Validate assembled or obtained big data sample
  • 1.1 Establish a sampling strategy for big data testing and identify a representative sample for big data testing
  • 1.2 Assemble or obtain sample of raw big data according to legislative requirements and organisational policies and procedures
  • 1.3 Validate big data sample from various sources to ensure that big data is correct
2. Validate big data sample process and business logic
  • 2.1 Align datasets to relevant parts of the organisation
  • 2.2 Implement data aggregation and segregation rules on a small set of sample data and datasets
  • 2.3 Consult with required personnel to clarify and resolve identified anomalies
  • 2.4 Conduct performance testing for data throughput, data processing and sub-component performance
3. Validate output of captured big data sample and record results
  • 3.1 Design, formulate and select suitable test scenarios and test cases to validate output of big data sample
  • 3.2 Implement selected test scenarios and test cases with big data sample using common testing tools and according to organisational procedures
  • 3.3 Isolate sub-standard data and correct data acquisition paths as required
  • 3.4 Generate and store results of validation activity and associated supporting evidence according to organisational policies and procedures, and legislative requirements
4. Optimise big data sample results and documentation
  • 4.1 Perform data cleansing on big data sample following testing according to industry practices and organisational procedures
  • 4.2 Collate validated output of testing, confirming absence of big data corruption in sample
  • 4.3 Recommend configuration optimisation changes based on performance testing results
  • 4.4 Communicate final sample results to required personnel
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