As data breaches continue to make headlines, it’s imperative for enterprises across all industries to securely manage their sensitive data. Increasingly stringent data security and privacy regulations make the consequences of a breach more dire. The challenge of protecting this data is further exacerbated by the exponential increase in the volume of enterprise data, particularly as data sprawls across environments used for development, testing, analytics, and other non-production use cases.
This guide explains why it’s important to mask your non-production data, what to look for in a masking solution, and how to transform application development in your organization with a DevOps test data management (TDM) approach.
- Understanding why you need to mask data
- Comparing common approaches for masking sensitive data including static masking, dynamic masking, and synthetic data
- Recognizing what Features to look for in a masking solution and why they’re important
- How a DevOps TDM approach can help your organization