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Elements and Performance Criteria

1. Review and clean data set
   • Identify and remove incorrect data input and formulate data according to task requirements
   • Confirm required data set parameter range according to task requirements
   • Run analytics and confirm that data set consistency according to task requirements
   • Remove any data values that are outside upper and lower threshold of acceptable range
   • Confirm consistency between digitally entered data and manually entered data
   • Identify and review over-writes according to organisational requirements
   • Review data set and confirm analytical suitability according to task requirements
   • Store data set securely according to organisational procedures, legislative requirements and industry standard practices
   • Obtain final task sign off from required personnel

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:

combine at least two data sets from different sources

confirm accuracy of the two combined data sets.

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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:

legislative requirements relating to data capture and storage, including data protection, security and privacy laws and regulations

organisational policies, procedures and protocols relating to protecting data integrity for:

data accuracy

identification of data over-writes

verifying data security

monitoring data discrepancies between different sources

digital versus manual data entry

monitoring data integrity

identifying where data breaches have occurred

ethical management and governance of data, including determining availability of data and confidentiality of data

compliance requirements and regulations relating to data loss

key components of policies in place for protecting confidential and private business information and intellectual property in data assets, including:

privacy policies

security policies

intellectual property policies

data analytics including feature extraction procedures.

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