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How can Data Quality be measured?

4. How can Data Quality be measured?

We measure Data Quality using Data Quality Dimensions and Business Rules.

Here are some of the most common Data Quality Dimensions to which Data should comply:

  • Completeness
  • Uniqueness / Duplication
  • Currency
  • Consistency
  • Accuracy

What is a Business Rule?

  • "A Business rule is a statement that defines or constrains some aspect of the business.
  • Business Rules describe the operations, definitions and constraints that apply to an organisation." Source: Ronald G. Ross

Each of these dimensions can and should be measured using automated software which checks every item against the defined Rules for that attribute and provides detailed statistics on each Data Quality Dimension. When we measure Data Quality we measure it in in terms of the DQ Dimensions AND the Business Rules. Results are reported back to the client in the form of a Scorecard intended to provide them with the overall status of the data in scope. The scorecard is presented graphically for ease of use by the stakeholders.

Here is an example of a very simple scorecard:

All AttributesRecord TotalWith Data%age
Customer Number4949100%
Customer Name4949100%
DOB494796%
Gender494898%
SA ID Number492551%
GenderCount%age
Unknown3163.30%
F918.40%
M816.30%
12.00%

  Case Study Results This Period

AttributeDQ Dimension
CompletenessUniquenessAccuracy
Customer ID100%100%100%
DOB96%N/AUnknown
Gender98%N/A34.70%
SA ID Number51%67%Unknown

 Case Study Thresholds

AttributeDQ Dimension
CompletenessUniquenessAccuracy
GreenAmberRedGreenAmberRedGreenAmberRed
Customer ID100%N/A<100%100%N/A<100%N/AN/AN/A
Gender80-100%60-79%<60%N/AN/AN/A80-100%60-79%<60%
SA ID Number80-100%60-79%<60%80-100%60-79%<60%80-100%60-79%<60%

The results of Assessment show that more than 60% of our Client Data do not have a valid Gender. This is the reason that Marketing are struggling to target Clients based on their Gender.

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