NTISthis.com

Evidence Guide: ICTDAT402 - Clean and verify data

Student: __________________________________________________

Signature: _________________________________________________

Tips for gathering evidence to demonstrate your skills

The important thing to remember when gathering evidence is that the more evidence the better - that is, the more evidence you gather to demonstrate your skills, the more confident an assessor can be that you have learned the skills not just at one point in time, but are continuing to apply and develop those skills (as opposed to just learning for the test!). Furthermore, one piece of evidence that you collect will not usualy demonstrate all the required criteria for a unit of competency, whereas multiple overlapping pieces of evidence will usually do the trick!

From the Wiki University

 

ICTDAT402 - Clean and verify data

What evidence can you provide to prove your understanding of each of the following citeria?

Review and clean data set

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

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Confirm required data set parameter range according to task requirements

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Run analytics and confirm that data set consistency according to task requirements

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Remove any data values that are outside upper and lower threshold of acceptable range

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Confirm consistency between digitally entered data and manually entered data

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Identify and review over-writes according to organisational requirements

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Review data set and confirm analytical suitability according to task requirements

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Store data set securely according to organisational procedures, legislative requirements and industry standard practices

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Obtain final task sign off from required personnel

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Assessed

Teacher: ___________________________________ Date: _________

Signature: ________________________________________________

Comments:

 

 

 

 

 

 

 

 

Instructions to Assessors

Required Skills and Knowledge

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.