[AG.DLM.4] Maintain data compliance with scalable classification strategies - DevOps Guidance

[AG.DLM.4] Maintain data compliance with scalable classification strategies

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Automated data classification includes using tools and strategies to identify, tag, and categorize data based on sensitivity levels, type, and more. Data classification aids in enforcing data security, privacy, and compliance requirements. Misclassification or lack of data classification can lead to data breaches or non-compliance with data protection regulations. Scaling this practice through automation enables organizations to catalog, secure, and maintain the vast amounts of data they process.

Use tagging strategies to catalog data effectively and help maintain visibility of data across different services and stages of the software development lifecycle. Put guardrails in place to enforce compliance with data classification and handling requirements, such as those related to data privacy and residency. Continuously monitor data at different stages - collection, processing, classification, and sharing - to ensure the right handling strategies are in place and are being followed.

For advanced use cases, AI/ML tools can provide automatic recognition and classification of data, especially sensitive data. This approach can reduce the need for manual, human intervention.

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