Application
This unit describes the skills and knowledge required to prepare and test data against an organisation’s requirements.
It applies to individuals who work in roles including, data analysts and data scientists, and run hypothesis testing on big data in a medium or large sized organisation.
No licensing, legislative or certification requirements apply to this unit at the time of publication.
Elements and Performance Criteria
1. Prepare to conduct significance test | 1.1 Analyse organisational requirements for significance testing and determine hypothesis for testing 1.2 Determine testing boundaries and data validation methods 1.3 Select all required data and its sources 1.4 Plan and document data extraction procedure 1.5 Plan and document significance testing activities according to organisational requirements |
2. Conduct testing | 2.1 Extract and secure data according to task requirements 2.2 Normalise and structure data according task requirements 2.3 Initiate data analysis and determine correct progression 2.4 Manipulate variables within data according to task requirements 2.5 Obtain testing results from required sources |
3. Report test findings | 3.1 Analyse test findings and determine testing has been completed according to test plan and task requirements 3.2 Analyse test findings and conclude hypothesis 3.3 Document testing activities and findings according to task requirements 3.4 Communicate findings with required personnel and seek and respond to feedback 3.5 Lodge documents according to organisational requirements |
Evidence of Performance
The candidate must demonstrate the ability to complete the tasks outlined in the elements, performance criteria and foundation skills of this unit, including evidence of the ability to:
plan and conduct a significance test on extracted and normalised data and conclude finding on at least two occasions.
In the course of the above, the candidate must:
identify and conduct data normalising methodologies
develop a hypothesis used for significance testing.
Evidence of Knowledge
The candidate must be able to demonstrate knowledge to complete the tasks outlined in the elements, performance criteria and foundation skills of this unit, including knowledge of:
data extraction methodologies
data normalising methodologies used in data analysis and data reporting
methodologies of securing and preparing data for data extraction
industry standard data analysis methodologies
technical requirements used in extracting different types of data
hypothesis development for significance testing
report writing for reporting significance testing in data analytics.
Assessment Conditions
Assessment must be conducted in a safe environment where evidence gathered demonstrates consistent performance of typical activities experienced in the customer service field of work and include access to:
hardware and software and components required for data analysis tasks
organisational data reporting style guide and reporting processes required for data reporting
a site where activities can be carried out.
data required for testing.
Assessors of this unit must satisfy the requirements for assessors in applicable vocational education and training legislation, frameworks and/or standards.
Foundation Skills
Oral communication | Uses listening and questioning techniques to seek and respond to feedback |
Reading | Analyses technical, manufacturer and organisational documentation to determine and confirm job requirements |
Writing | Prepares required documentation conveying explicit information, requirements and recommendations according to organisational requirements |
Planning and organising | Uses a formal, logical planning processes together with an increasingly intuitive understanding of context |
Problem solving | Uses nuanced understanding of context to recognise anomalies and subtle deviations to normal expectations, focusing attention and remedying problems as they arise |
Self-management | Takes full responsibility for identifying and considering relevant organisational protocols and requirements Uses systematic processes, setting goals, gathering required information and identifying and evaluating options against agreed criteria |
Technology | Demonstrates an understanding of principles, concepts, language and practices associated with the digital world |
Sectors
Data analytics