Data Masker for SQL Server is a powerful tool that can help protect sensitive data and ensure compliance with regulations such as GDPR. In this article, we will explore a common technique for anonymizing date data using Data Masker.

Masking the Birthdate

Let’s say we have a database with a table called dbo.DM_EMPLOYEE that contains columns for person_id, full_name, and birth_date. As we move this data to QA and development environments, we want to ensure that even if we mask the id or name, the birthdate does not reveal too much information about the user.

To accomplish this, we can use Data Masker to anonymize the birthdate. We will create a masking rule that is a substitution rule and apply it to the dbo.DM_EMPLOYEE.birth_date column.

There are several datasets available in Data Masker that we can choose from. For this example, let’s use the Data Variance (Random) dataset. This dataset will assign a random date within a specified variance to each row in the table.

After running the masking rule, we can see that the birthdate values have been anonymized. Each row now has a random date within the specified variance.

Using Data Masker with SQL Provision

Now that we have successfully anonymized the birthdate data, we can use SQL Provision to create a new image from the original data. In the modification step of SQL Provision, we can add the dataset we created in Data Masker to ensure that every clone made from this process includes random birthdays that are close, but not correct.

By combining Data Masker with SQL Provision, we can automate the process of anonymizing data and creating realistic test environments. This frees up developers from tedious tasks and allows them to work with large datasets without the hassle of restoring large databases.

Conclusion

Data Masker for SQL Server is a valuable tool for anonymizing sensitive data. By using techniques like the one described in this article, you can reduce the risk of exposing personal information and ensure compliance with data protection regulations.

If you’re interested in trying out Data Masker and SQL Provision, you can download an evaluation today and explore the possibilities of implementing your own masking requirements.

Stay tuned for more articles on Data Masker and other SQL Server topics!