Part of Data Quality Maturity Index (DQMI) methodology
Appendix 1: Example of DQMI calculation
| Dataset | Data item | Number of records | Valid and complete | Defaults | Defaults in excess (calculated) | Threshold for proportion of defaults (%) | Data item score (calculated) | Coverage of dataset (calculated) |
|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 2,500 | 2,400 | 100 | 50 | 2.0 | 94.0 | 1.0 |
| 1 | 2 | 2,500 | 2,500 | 100 | 0 | 100.0 | 100.0 | 1.0 |
| 1 | 3 | 2,500 | 2,000 | 100 | 100 | 0.0 | 76.0 | 1.0 |
| 2 | 1 | 1,000 | 900 | 900 | 900 | 0.0 | 0.0 | 1.0 |
| 2 | 2 | 1,000 | 800 | 800 | 0 | 100.0 | 80.0 | 1.0 |
| 2 | 3 | 1,000 | 900 | 450 | 450 | 0.0 | 45.0 | 1.0 |
| 2 | 4 | 1,000 | 1,000 | 100 | 65 | 3.5 | 93.5 | 1.0 |
| 3 | 1 | 10,000 | 10,000 | - | - | - | 100.0 | 1.0 |
| 3 | 2 | 10,000 | 10,000 | - | - | - | 100.0 | 1.0 |
| 4 | 1 | - | - | - | - | - | - | - |
| 5 | 1 | - | - | - | - | - | - | - |
| 7 | 1 | 50,000 | 50,000 | 100 | 0 | 2.0 | 100.0 | 1.0 |
| 7 | 2 | 50,000 | 49,000 | 5,000 | 0 | 100.0 | 98.0 | 1.0 |
| 7 | 3 | 50,000 | 45.000 | 5,000 | 3,250 | 3.5 | 83.5 | 1.0 |
Note: '-' denotes that no data was expected
Formulae
\(Defaults\ in\ excess = Total\ Defaults\ - (Threshold\ *\ Number\ of\ Records)\)
\(Data\ Item\ Score = ({Number\ of\ valid\ and\ complete\ records - defaults\ in\ excess\ \over Number\ of\ records}) * 100\)
\(DQMI = \frac{1}{n} \Sigma_{i=1}^n({Number\ of\ valid\ and\ complete\ records - defaults\ in\ excess \over\ Number\ of\ records})_i \ *\ \frac{1}{n}\Sigma^n_{i=1}(C)_i \ *\ 100\)
Where n is the number of data items for which data was submitted, 𝑖 is the index number of each of those data items and C is coverage.
DQMI calculation
\(DQMI = [ ({1 \over 12}) * (0.94 +1.0 +0.76 + 0 +0.8 + 0.45 +0.935 + 1.0 + 1.0 + 1.0 +0.98 + 0.835)] *\)
\( [({1\over 12}) * (1 + 1 + 1 + \frac {1}{3} + \frac {1}{3} + \frac {1}{3} + \frac {1}{3} + \frac {1}{3} + \frac {1}{3} + \frac {2}{3} + \frac {2}{3} + \frac {2}{3})] * 100\)
\(DQMI = [( {1 \over 12}) * (9.7)] * [({1 \over 12}) * (7)] * 100 = 47.2\)
Last edited: 11 October 2021 5:22 pm