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:
What is a Business Rule?
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 Attributes | Record Total | With Data | %age |
---|---|---|---|
Customer Number | 49 | 49 | 100% |
Customer Name | 49 | 49 | 100% |
DOB | 49 | 47 | 96% |
Gender | 49 | 48 | 98% |
SA ID Number | 49 | 25 | 51% |
Gender | Count | %age |
---|---|---|
Unknown | 31 | 63.30% |
F | 9 | 18.40% |
M | 8 | 16.30% |
1 | 2.00% |
Case Study Results This Period
Attribute | DQ Dimension | ||
---|---|---|---|
Completeness | Uniqueness | Accuracy | |
Customer ID | 100% | 100% | 100% |
DOB | 96% | N/A | Unknown |
Gender | 98% | N/A | 34.70% |
SA ID Number | 51% | 67% | Unknown |
Case Study Thresholds
Attribute | DQ Dimension | ||||||||
---|---|---|---|---|---|---|---|---|---|
Completeness | Uniqueness | Accuracy | |||||||
Green | Amber | Red | Green | Amber | Red | Green | Amber | Red | |
Customer ID | 100% | N/A | <100% | 100% | N/A | <100% | N/A | N/A | N/A |
Gender | 80-100% | 60-79% | <60% | N/A | N/A | N/A | 80-100% | 60-79% | <60% |
SA ID Number | 80-100% | 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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