How can data integration help address data security and privacy issues and risks?
Data integration is the process of combining data from different sources into a unified and consistent view. It can enable better decision making, analytics, and business intelligence, but it also comes with some challenges and risks, especially in terms of data security and privacy. How can data integration help address these issues and protect the sensitive and valuable data of your organization and customers? Here are some key aspects to consider.
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Effective data masking:Integrating data allows for consistent application of masking techniques, safeguarding sensitive info across all datasets. You can automate this process, reducing human error and bolstering privacy compliance.
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Centralized access governance:A "common access layer" centralizes governance, simplifying policy management. It ensures that only the right eyes see sensitive data by automating and enforcing access policies across various data platforms.