Table 7 Example of exploratory quality profiling scenarios
From: Big data quality framework: a holistic approach to continuous quality management
# | Predefined scenario actions (PPAF) | Scenario actions PPA functions description | Execution order |
|---|---|---|---|
1 | DeleteCols(dqd,“ > ”,TL) | Drop all columns or attributes with dqd ratio greater than TL: Tolerance Level | 1 |
2 | DeleteRows(dqd,“ > ”,TL) | Drop all Observations or rows with dqd ratio greater than TL | 1 |
3 | DeleteRows(dqd,“ > ”,TL) DeleteCols(dqd,“ > ”,TL) | Drop all Observations, then Attributes with dqd ratio greater than TL | 1 2 |
4 | DeleteRows(dqd,“ > ”,TL) | Drop all Observations or rows with dqd ratio greater than TL | 1 |
newdqd = Re-Evaluate () | Recalculate the new dqd ratio after the row drop | 2 | |
DeleteCols(newdqd,“ > ”,TL) | Drop all columns or attributes with newdqd ratio greater than TL | 3 | |
5 | DeleteCols(dqd,“ > ”,TL) | Drop all attributes with dqd ratio greater than TL | 1 |
newdqd = Re-Evaluate () | Recalculate the new dqd ratio after the attributes drop | 2 | |
DeleteRows(newdqd,“ > ”,TL) | Drop all observations with newdqd ratio greater than TL | 3 |