Column Profile Concepts Overview
A column profile determines the characteristics of columns in a data source, such as value frequency, percentages, and patterns.
Column profiling discovers the following facts about data:
- •The number of null, unique, and non-unique values in each column, expressed as a number and a percentage.
- •The patterns of data in each column and the frequencies with which these values occur.
- •Statistics about the column values, such as the maximum and minimum lengths of values and the first and last values in each column.
- •Documented and inferred data types along with any data conflicts.
- •Pattern and value frequency outliers.
Use column profile options to select the columns on which you want to run a profile, set data sampling options, and set drill-down options when you create a profile.
You can add comments and tags to a profile and to the columns in a profile. You can assign business terms to columns.
The Model repository locks profiles to prevent users from overwriting work with the repository profile locks. The version control system saves multiple versions of a profile and assigns a version number to each version. You can check out a profile and then check the profile in after making changes. You can undo the action of checking out a profile before you check the profile back in.
A rule is business logic that defines conditions applied to source data when you run a profile. You can add a rule to the profile to validate data.
Create scorecards to periodically review data quality. You create scorecards before and after you apply rules to profiles so that you can view a graphical representation of the valid values for columns.