Product articles Masking Data for Development and Testing
Getting Started with Data Masker for SQL Server: I Want to Mask A Database
Grant Fritchey explains what's involved in masking a SQL Server database. It can seem a daunting task, but it all becomes a lot more logical if you start from a plan, based on agreed data classifications, and then use a tool like Data Masker to implement the masking, and track progress. Read moreGetting Started with SQL Data Masker: I Need to Mask some Columns
Grant Fritchey explains the core rules and features of Data Masker, and how you go about using them to mask columns, so that when the data is used outside the production system it could not identify an individual or reveal sensitive information. Read moreManaging Data Masking Rules in Larger Teams using Source Control
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
Practical steps for end-to-end data protection
If you plan to make production data available for development and test purposes, you'll need to understand which columns contain personal or sensitive data, create a data catalog to record those decisions, devise and implement a data masking, and then provision the sanitized database copies. Richard Macaskill show how to automate as much of this process as possible. Read more
How to Provision a Set of Databases to Multiple Azure-based Servers
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 moreHow to do Accurate Address Masking using Data Masker
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 moreA Basic Technique for Masking Address Data using Data Masker
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 moreSpoofing Realistic Credit Card Data for your Test Systems using Data Masker
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 moreBuilding Better Test Data with SQL Provision
Steve Jones show how a team might use SQL Provision to build consistent, compliant, useful databases, on demand, for development and test environments. Read moreRedgate Hub
-
Product Articles
Tips and how-to guides for Redgate products
-
University
Easy to follow video courses
-
Events
Join us online, or get sponsored
-
Forums
Ask, discuss, and solve questions about Redgate's tools
-
Community
Develop your skills and meet Redgate Advocates and Friends
-
Simple Talk
In-depth articles and opinion from Redgate's technical journal