Mask Stored Data

As a test data engineer, use the Fast Data Masker UI to access, set up, save, and run the masking options for the data stored in different data sources—relational (for example, Oracle and Microsoft SQL Server) and flat files (for example, fixed-width and JSON files).
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As a test data engineer, use the Fast Data Masker UI to access, set up, save, and run the masking options for the data stored in different data sources—relational (for example, Oracle and Microsoft SQL Server) and flat files (for example, fixed-width and JSON files).
The process that you follow in Fast Data Masker to mask the data is as follows:
  1. Input:
     Connect Fast Data Masker to the data source.
    To get started with the masking process, you must first connect your Fast Data Masker instance to the data source that contains the data you want to mask. You establish this connection with the help of a connection file. This connection file includes all the relevant information about the data source. You create this connection in the Fast Data Masker UI. After you create this file, you can use it to connect to the data source whenever you want.
  2. Rule Definition:
     Define masking rules.
    You define all the masking rules by using various available operations (for example, masking functions and options) in the Fast Data Masker UI. After you define the rules, you run the masking job to mask the stored data in the data source.
  3. Output:
     Verify the masked data.
    You access the data source and verify the output; that is, the masked data. Ensure that you note the pre-masked data before you run the masking job so that you can verify it with the masked data after the masking job completes.
Note:
This process is a generic process that is outlined here for easier understanding of the masking process in the context of Fast Data Masker. You might need to perform additional steps depending on your unique data source.