Data Masking Pitfalls for SQL Data Generator Applications
Developing a production database requires extensive optimization. With the growing concerns about data privacy and new regulations such as the Global Data Protection Requirement (GDPR), these databases must be created with privacy safeguards in place. You need to use a few different data anonymization techniques to accomplish this with a standard SQL database.
SQL data generator tools are frequently used for data anonymization. Here is the process for using data anonymization with SQL generators.
Conduct a data audit and mark data sets that require masking
Anonymization tokens are often necessary, but they also take time to set up. Applying data masking to every data set would be an unnecessarily time intensive and cumbersome process.
You need to begin by taking an inventory of all current and future data sets. Mark data that will need to be anonymized with your SQL generator. Other data can be easily copied from your production database.
Benefits of using an SQL generator for producing sensitive data
The biggest mistake that Data administrators make when anonymizing SQL entries is copying sensitive data and trying to add the anonymization tokens after the fact. This creates a couple of security risks, which are listed below.
Data may be hijacked if the server is compromised
There is ...
Read More on Datafloq
SQL data generator tools are frequently used for data anonymization. Here is the process for using data anonymization with SQL generators.
Conduct a data audit and mark data sets that require masking
Anonymization tokens are often necessary, but they also take time to set up. Applying data masking to every data set would be an unnecessarily time intensive and cumbersome process.
You need to begin by taking an inventory of all current and future data sets. Mark data that will need to be anonymized with your SQL generator. Other data can be easily copied from your production database.
Benefits of using an SQL generator for producing sensitive data
The biggest mistake that Data administrators make when anonymizing SQL entries is copying sensitive data and trying to add the anonymization tokens after the fact. This creates a couple of security risks, which are listed below.
Data may be hijacked if the server is compromised
There is ...
Read More on Datafloq
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