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Follow the links below to find material targeted to the unit's elements, performance criteria, required skills and knowledge

Elements and Performance Criteria

1. Determine purpose and scope of big data analysis
   • Determine organisational requirements for big data analysis
   • Identify internal and external sources of big data to be analysed according to organisational policies and procedures and legislative requirements
   • Establish and confirm parameters to be applied in analysis according to organisational policies and procedures
2. Analyse initial trends and relationships in captured big data
   • Categorise and prepare captured big data for analysis
   • Extract and transform structured and unstructured big data in preparation for data analysis
   • Analyse big data and derive insights into trends using required tools and dashboards
3. Finalise big data analysis
   • Conduct statistical analysis to confirm accuracy of big data analysis
   • Isolate and remove identified incorrect results
   • Develop report on key outcomes from analysis
   • Store analytics results, associated report and supporting evidence according to organisational policies and procedures, and legislative requirements

Performance Evidence

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:

analyse trends and relationships in two different sets of big data: one transactional and one non-transactional

report on the results and insights from each analysis

store analytics results from each of the two big data sets according to organisational policies and procedures.

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Knowledge Evidence

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:

purpose and benefits to organisation of big data analysis

legislative requirements relating to analysing big data, including data protection and privacy laws and regulations

organisational policies and procedures relating to analysing big data, including for:

identifying big data sources

establishing and confirming categories to be applied in analysis

analysing data to identify business insights

integrating big data sources, including structured, semi-structured, and unstructured

combining external big data sources, such as social media, with in-house big data

reporting on analysis of big data, including the use of suitable reporting and business intelligence (BI) tools

industry protocols and procedures required to write basic queries to search combined big data

required analytical techniques and tools to analyse transactional and non-transactional big data, including:

data mining

ad hoc queries

operational and real-time business intelligence

text analysis

statistical concepts relating to big data analytics

relationship between raw big data and big datasets

common models and tools to analyse big data, including features and functions of Excel software for advanced analytics of external big data

sources of uncertainty within big data

classification categories of analytics, including text, audio/video, web and network

role of technology and automation tools in performing big data analytics.

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