Product articles Data Masker
Getting 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 moreMeeting your CCPA needs with Data Classification and Masking
This article will explain how to import the data classification metadata for a SQL Server database into Data Masker, providing a masking plan that you can use to ensure the protection of all this data. By applying the data masking operation as part of an automated database provisioning process, you make it fast, repeatable and auditable. 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
How 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 moreCreating Multiple Masked Databases with SQL Provision
Chris Unwin explains how SQL Provision can create copies of multiple databases, each masked consistently, and deliver them as a group. This is useful when, for example, you are working with a Data Warehouse that contains several cross-database relationships. Read moreApproaches to masking email addresses
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 moreMasking Dates in a Non-Production Database
Gerry Leith explores what’s required for the effective masking of dates and times in your data. Read moreRedgate Hub
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