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In addition to attribute analysis, functional dependency analysis, and referential analysis, OWB offers data rule profiling. Data rule profiling enables you to create rules to search for profile parameters within or between objects.
This is very powerful as it enables you to validate rules that apparently exist and are defined by the business users. By creating a data rule, and then profiling with this rule you can verify if the data actually complies with the rule, and whether or not the rule needs amending or the data needs cleansing.
For example, the HR department might define a rule that states that Income = Salary + Bonus for the Employee table shown in Table: Sample Employee Table. You can then catch errors such as the one for employee Alison.
Sample Employee Table
| ID | Name | Salary | Bonus | Income |
|---|---|---|---|---|
|
10 |
Alison |
1000 |
50 |
1075 (error) |
|
20 |
Rochnik |
1000 |
75 |
1075 |
|
30 |
Meijer |
300 |
35 |
335 |
|
40 |
Jones |
1200 |
500 |
1700 |
|
See Also: Data Cleansing and Correction with Data Rules in Oracle Warehouse Builder Data Modeling, ETL, and Data Quality Guide |