SQL Data Catalog 2.0 provides a simple, policy-driven approach to data protection, through data masking. It can now automatically generate the static masking sets that Data Masker will use to protect your entire database, directly from the data classification metadata held within the catalog. Read more
What if you have several people in the team who are responsible for data security across your databases, and they need to work together to develop and maintain the data masking configurations, which must then be applied consistently as part of an automated provisioning process? How should they do it? The solution turns out to be simple: source control. Read more
The first time you approach the task of data masking, it can seem daunting. You've identified your sensitive columns, but how do you decide on the best data masking strategy? Which rules do you need in your data masking set? Data Masker for SQL Server makes it easy to decide. Read more
Grant Fritchey shows how to provision a group of interdependent databases, masked to protect sensitive or personal data, to each machine in an Azure-based test cell. Read more
Grant Fritchey shows how to adapt a data masking process, for address data, so that it incorporates knowledge of the data distribution in the real data. The result is fake address data, with an accurate distribution, for use in development and testing work. Read more
Grant Fritchey provides a simple way to create fake address information that still looks real. The compromise is that it uses random data distributions and doesn't maintain any correlation between postal codes, states and cities, so won’t accurately reflect the real address data. Read more
Grant Fritchey shows how to use Data Masker to create fake credit card data that not only looks like the real thing, but also has the right distribution, so will act like it too, when we query it. Read more
Steve Jones show how a team might use SQL Provision to build consistent, compliant, useful databases, on demand, for development and test environments. Read more
Steve Jones shows a simple way to provision full size databases for developers, using production like data that has been masked automatically as part of the provisioning process. Read more
Chris Unwin explains the basic approaches to anonymizing email addresses, and shows how Data Masker can generate realistic email addresses, based on faked names, and even retain the correct distribution of email providers. Read more
