Some say data is an asset; others say it is a liability.
In truth, it’s more like water, not inherently good or bad – but it can leak and move into places you don’t want it to go.
With the proliferation of data privacy regulations worldwide making the protection of confidential, personally identifiable, and regulated data top of mind even for ordinary people, organizations must learn how to manage, control, and use their data responsibly.
The question is how?
This white paper offers practical guidance on how to dynamically de-identify sensitive data. You’ll learn:
- Why de-identification is important for data analytics
- Practical guidance on how and when to use redaction, masking, tokenization, etc.
- Encryption’s role in data privacy
- When and why to choose static vs. dynamic data de-identification
The considerations and techniques presented here will help data teams who are responsible for provisioning data to the business for analytics purposes while protecting data from unlawful or other unauthorized access.