In its ongoing effort to help the increasing number of companies and organizations that need to use data masking in their development environments, Redgate has released another update for its Data Masker for SQL Server tool.
The twelfth release this year, the new version makes it much easier for users to identify the best data masking rules to fit their needs. Alongside the 15 updates that were released in 2018, it’s part of the development team’s goal to ensure the tool ties in as closely as possible with customer requirements and workflows.
While common in sectors like financial services and healthcare, the need to mask data in every sector was brought to prominence by the introduction of the GDPR and other recent data protection legislation. Personally identifiable information now has to be protected using measures like pseudonymization and this presents a challenge when research repeatedly reveals that developers like to use a copy of the production database to test their proposed changes against.
Redgate’s 2019 State of Database DevOps Survey, for example, showed that 65% of the data in development and test environments is a copy of the production data. This broadly matches a poll by prominent SQL Server consultant, Brent Ozar, which revealed that 57% of the 901 respondents use a copy of production data in development.
The new requirement to mask that data has increased the interest in data masking tools and Gartner’s July 2018 Market Guide for Data Masking predicts that: “By 2021, the global enterprise use of data masking or similar de-identification techniques will increase to 40%, an increase from 15% in 2017.”
The rise in the adoption of data masking also, however, brings challenges because the use-cases and requirements vary by sector, by organization and company size, and by the type of data that needs to be masked. As a result, the Redgate development team behind Data Masker for SQL Server is constantly looking at how the tool can be improved for its many different users.
Recent releases of the tool have addressed everything from enhancements to user-defined datasets to masking JSON data, and from adding datasets for NHS numbers to providing information on how masking rules are supposed to be used.
As James Murtagh, Redgate Product Marketing Manager, comments: “Data masking has moved from a specialist requirement to an everyday one, and as more and more companies and organizations are obliged to adopt it, so we need to make sure our solution can help them.”
The development team are now working on making it easier to get started with Data Masker so that IT teams can introduce the tool to their normal workflows faster and make data masking a standard part of their development process.