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Strategy

Data Masking in Principle

This is the first of two articles to describe the principles and practicalities of masking data in databases. It explains why an organization sometimes needs masked data, the various forms of masked data we can use, the sort of data that needs to be masked, and the potential pitfalls. Read more

Data Masking in Practice

This article takes a strategic look at common SQL data masking techniques, and the challenges inherent in masking certain types of sensitive and personal data, while ensuring that it still looks like the real data, and retains its referential integrity, and distribution characteristics. It also explains, briefly, with references, the tools that one can use to mask different types of data and how to provision development and test machines with these 'de-sensitized' databases, or alternatively to produce fake data that looks like the real thing, but in fact is generated randomly. Read more

Protecting production data in non-production environments

Grant Fritchey discusses the need to ‘shift left’ the database and associated database testing, while keeping sensitive data secure when it is outside the production environment, and how SQL Provision can help you achieve this. Read more