Six Sigma Metrics for Data Profiling

When you perform data profiling, the number of defects and anomalies discovered are shown as Six Sigma metrics. For example, if data profiling finds that a table has a row relationship with a second table, the number of records in the first table that do not adhere to this row-relationship can be described using the Six Sigma metric.

Six Sigma metrics are calculated for the following measures in the Data Profile Editor:

• Aggregation: For each column, the number of null values (defects) to the total number of rows in the table (opportunities).

• Domains: For each column, the number of values that do not comply with the documented domain (defects) to the total number of rows in the table (opportunities).

• Referential: For each relationship, the number of values that do not comply with the documented foreign key (defects) to the total number of rows in the table (opportunities).

• Functional Dependency: For each column, the number of values that are redundant (defects) to the total number of rows in the table (opportunities).

• Unique Key: For each unique key, the number of values that do not comply with the documented unique key (defects) to the total number of rows in the table (opportunities).