Data Masking in Azure

Looking for the fastest and easiest data masking tool for cloud databases like Azure?

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  • Supporting Azure SQL databases
  • High performance on large data sets
  • Automate Data Masking in CI/CD pipelines
  • Including Synthetic Data Generation
  • Preserve data characteristics
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What is data masking in Azure

Databases are increasingly being placed in the cloud. In that case, no server is installed with a database on it, but a database is purchased as a service. For example, Azure SQL or Amazon RDS. These database technologies can be used in combination with DATPROF Privacy when using a straightforward connection method. In this way, the cloud databases of your organization are also masked with the possibilities of an on-premise database.

 

Data masking tools Azure

Azure offers some native data masking tools, and can perform simple pre-defined column based masking duties. This can be sufficient for simple data sets, but falls short when advanced masking logic is required or complex data sets need to be processed.

Azure often uses standard values when masking data. Some examples include:

  • Defaulting dates to 01-01-1900
  • XMLs files to <masked/>
  • Standard values for SQL columns that have a standard value defined
  • Hashing credit card data (ex. XXXX-XXXX-XXXX-XXXX-1234)

Dynamic data masking is possible, but requires users to create SQL queries in the database, and suffers from the same functional limitations. Due to lacking a filtered interface that allows users to tackle large datasets one schema at a time, developers are forced to select each masking rule individually.

 

How to do data masking in Azure

DATPROF Privacy has native support for Azure SQL databases and can easily be connected to an existing instance through an ODBC connection. With a dedicated interface for data masking and synthetic data generation developers are able to compartmentalize large datasets and tackle them in a structured and efficient manner.

Where Azure falls short in terms of masking customizability Privacy offers users deep, intuitive functions which eliminate the need for querying the database manually. Be it through regular expressions, SQL expressions, or one of the many preconfigured masking and generation functions, we enable your data to shine and comply with even the most stringent of requirements without overwhelming users with complicated syntax.

 

How the cloud enables a new generation of Test Data Management

Azure SQL databases are automatically scalable and fast-deploying instances which can be easily created and dropped at a moment’s notice. Because of this, it becomes easier to quickly create, partition space for, and connect to a database instance specifically made for a testing team.

Because DATPROF can be deeply integrated with other applications through our RESTful API or through in-software Workflow automation templates it’s easier than ever to create, populate, mask and deallocate database instances at the click of a button.

Compared to statically hosted databases, Azure databases can be configured to be billed per usage units. This translates in lower costs and less overhead for database instances which are used sporadically. Need to test a new software release once every six months? With automatically scaling database instances you eliminate the risk of paying for unused storage, and can easily clean up instances which are no longer needed.

 

Azure data masking example

Watch our technical product demonstration to see a data masking tutorial. DATPROF Privacy can connect directly to your Azure database to mask and generate data. Some commonly used masking and generation techniques in are shown in this demo. Download your 14-day free trial to see the data masking result in your database!

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Enable test teams with high quality masked production data and synthetically generated data for compliance.

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