Data masking is a way of securing sensitive data during the development or testing phases of a database development project. It is often performed as a security or compliance measure that protects important information. By masking valid production data, you can provide a copy of the data that is “scrambled” but still represents your production environment.
DB Change Manager lets you specify masking rules for moving data between a source and a target in a data comparison job. You can set rules for individual columns, tables, and entire databases. When you run a data comparison with the Automatically Synchronize option on, the data on the target is replaced with data from the source and any items configured with a masking rule will be masked. You can then use the masked data in your development and testing environments.
The following tasks describe how to create masked data:
Use the Data Comparison Job Editor to define a masking job.
To start creating a new Data Masking Job:
The name of the job distinguishes it between other jobs in the application environment.
To name a masked data job
The Job Sources section of the Data Comparison Job Editor contains the Data Comparison Source box, which identifies the original data source, and Target Data Source box, which identifies the data source where the data is altered.
To specify source and target data sources
Prior to running a masking job, set it to automatically clear all the data on the target and replace it with new, masked data.
To set synchronization
Use the Mappings tab to specify the tables to mask. You can apply a Default Masking Rule to selected columns using the pulldown menus.
The options are:
Use the check boxes in the left-hand column to de-select any columns that you do not want to include in the data masking job process.
To specify mapping options
You can specify different masking rules for different columns.
To specify a masking rule for a column
To execute the data masking job
You can see the masked data by running a new Data Comparison job and looking at the changes. For more information, see Comparing data.
For rows that do not have masking applied, you should see “0” in the Different column of the Results Overview box. For rows that are masked, you should see the number of rows that changed.
In the Selected Table box, you can see the masked data in the target table. For example, the First and Last Name data shown below was masked using the Randomize setting.
| | | | | | | |