![]() ![]() Then, you forward the tested backup to the necessary environments to restore it and use it for development and testing. That stage must ensure that all data are impersonal, and the secret data are changed.Īfter that stage, you can return to step 5 again for the tested database in the protected non-production environment. For instance, step 6 requires a specific, protected environment for preliminary testing. However, the algorithm becomes more complicated after step 5. Deliver and restore the backup in the necessary environment.Make a backup of the newly created database.Sanitize and change the secret data in the new database.Copy the necessary data from the production database into the newly created database.Create a scheme in that newly created database – the same system as that from the production database.Data copying and altering in a production databaseįirst, let’s define the general algorithm of copying and changing the data from the production environment. Now, let’s review in detail both the approaches to the data filling in databases for testing and development. This way, Approach 1 produces Approach 2. Basing on them, you can define how to generate the test data that would be like the real data by their looks, properties, and interrelations. On the other way, you can analyze impersonal sanitized data taken from the production database. It becomes problematic to predict changes in the entire information system’s functionality in the future. However, this approach does not let you increase the database itself many times. It allows us to analyze everything precisely and, therefore, to make conclusions and prognosis accordingly. ![]() The advantage of Approach 1 is that it approximates the data and their distribution by different criteria to the production database. It means generating the test data similar to the real data in look, properties, and interconnections. This way, you ensure the data and erase confidential data.
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