In my previous post "How to create Test Data", I explained the concept of creating test data directly from the production data. In this post we will concentrate on the Top 3 challenges in using the Production data for testing purposes.
This is by far the most crucial challenge of using Production data in Test Environments. Production data can contain a lot of sensitive information. Even though the data sets will be rich in nature in the Production database, the very thought of using production data involves a lot of risk. For ex. if you are testing an application for a bank, production data will contain real customer information like Names, Addresses, Account Numbers, Balances, Credit Card Numbers, etc. As you can see, if you try to use these data for testing, it exposes huge security risks for the bank. So how do we overcome this, the answer is Data Masking.
Data Masking is the process of masking of the sensitive fields from the complete data set. Please read my future post on Data Masking and the Techniques used for Data Masking for more details. The following figure depicts the data security challenge and the approaches.
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| Data Security Challenge |
