Addressing the perils of PII with the De-Identified Data lake
When done right, data masking should empower your business, not hinder it.
We are currently in what’s being described as a “data economy,” described as the trade in data between organizations and governments, and derivative data products (algorithms, insights, applications) arising from data flows that were previously unavailable. In the data economy, innovation is at odds with privacy, with a premium placed on innovation in many cases.
Learn how AWS and Data and Analytics Competency Partners have a broad approach to data governance based on an architecture called the De-Identified Data Lake (DIDL). A de-identified data lake solves the data privacy problem by de-identifying and protecting sensitive information before it even enters a data lake.
- Introduction into the DIDL and Architecture
- The DIDL Data Governance Process
- Customer Success Story
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