Assessor Resource

ICTDAT402
Clean and verify data

Assessment tool

Version 1.0
Issue Date: May 2024


This unit describes the skills and knowledge required to clean and verify data obtained from a variety of sources. It involves the use of analytics and review to ensure data quality for an organisation is according to industry practices and organisational policies, procedures and protocols.

It applies to data analytics specialists who work within in a broad range of industries and are responsible for processing data sets for a business.

No licensing, legislative or certification requirements apply to this unit at the time of publication.

You may want to include more information here about the target group and the purpose of the assessments (eg formative, summative, recognition)


Evidence Required

List the assessment methods to be used and the context and resources required for assessment. Copy and paste the relevant sections from the evidence guide below and then re-write these in plain English.

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.

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.

Skills in this unit must be demonstrated in a workplace or simulated environment where the conditions are typical of those in a working environment in this industry.

This includes access to:

information and data sources to inform data analysis

information and telecommunications equipment required to analyse data

industry standards, organisational procedures, and legislative requirements.

Assessors of this unit must satisfy the requirements for assessors in applicable vocational education and training legislation, frameworks and/or standards.

Submission Requirements

List each assessment task's title, type (eg project, observation/demonstration, essay, assingnment, checklist) and due date here

Assessment task 1: [title]      Due date:

(add new lines for each of the assessment tasks)

Assessment Tasks

Copy and paste from the following data to produce each assessment task. Write these in plain English and spell out how, when and where the task is to be carried out, under what conditions, and what resources are needed. Include guidelines about how well the candidate has to perform a task for it to be judged satisfactory.

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.

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.

Skills in this unit must be demonstrated in a workplace or simulated environment where the conditions are typical of those in a working environment in this industry.

This includes access to:

information and data sources to inform data analysis

information and telecommunications equipment required to analyse data

industry standards, organisational procedures, and legislative requirements.

Assessors of this unit must satisfy the requirements for assessors in applicable vocational education and training legislation, frameworks and/or standards.
Copy and paste from the following performance criteria to create an observation checklist for each task. When you have finished writing your assessment tool every one of these must have been addressed, preferably several times in a variety of contexts. To ensure this occurs download the assessment matrix for the unit; enter each assessment task as a column header and place check marks against each performance criteria that task addresses.

Observation Checklist

Tasks to be observed according to workplace/college/TAFE policy and procedures, relevant legislation and Codes of Practice Yes No Comments/feedback
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 

Forms

Assessment Cover Sheet

ICTDAT402 - Clean and verify data
Assessment task 1: [title]

Student name:

Student ID:

I declare that the assessment tasks submitted for this unit are my own work.

Student signature:

Result: Competent Not yet competent

Feedback to student

 

 

 

 

 

 

 

 

Assessor name:

Signature:

Date:

Assessment Record Sheet

ICTDAT402 - Clean and verify data

Student name:

Student ID:

Assessment task 1: [title] Result: Competent Not yet competent

(add lines for each task)

Feedback to student:

 

 

 

 

 

 

 

 

Overall assessment result: Competent Not yet competent

Assessor name:

Signature:

Date:

Student signature:

Date: