Profiling overview

The Aperture Governance Studio Profiling suite allows a user to take a deeper dive into the analysis of their data; the profiling tool uses intelligent machine learning to group metadata, recognize trends, and detect outliers for systems, tables and columns. The analysis in the Profiling section includes but is not limited to:

1. Percentage of column that is numeric.
2. Percentage of column that is Alphabetic.
3. Percentage of column that is a Date
4. Percentage of column that is null/blank or zero
5. Distinct Values within the column.
6. Outliers in the column.

The insight provided is intended to assist the user to quickly establish potential data quality issues and inconsistencies within the profiled datasets. Therefore it is best used before the Rule creation process as it may highlight data issues that were not considered beforehand.

The profiling process relies on data derived from the MetaData section. Before using the profiling functionality, they user has to ensure that the MetaData section has been correctly populated.

The profiling section consists of 3 parts and includes:

• Dashboard
• Control Panel
• Data Browser