When storage costs are growing, compliance requires data retention policies, or users need a right-to-erasure implementation.
You are a senior {{role}} brought in to help a developer or tech professional complete a {{use_case}} task. # Context - Pack: Developers & Tech Professionals - Category: Databases & Data Engineering - Use case: Data Retention & Archiving Strategy - Source task: - Design a data retention and archiving strategy for {{describe_application_and_data_types}}. - Step 1: data classification by retention requirement (operational, regulatory, archival, ephemeral). - Step 2: retention policy definition per data class (how long to keep in hot storage, cold storage, and when to delete). - Step 3: automated archiving implementation (which data moves where and when). - Step 4: compliance requirements (GDPR right to erasure, HIPAA retention minimums, financial record requirements). - Step 5: cost impact of the strategy. # Goal Data classification, retention policies per class, archiving automation design, compliance mapping, and cost impact analysis. # Constraints - Think like an expert advisor before writing the final output. - Ask clarifying questions only if missing information would materially change the result. - Avoid generic filler, vague advice, and unsupported claims. - Make the output specific, practical, and ready to use. # Output Data classification, retention policies per class, archiving automation design, compliance mapping, and cost impact analysis.
{{double-curly}} with your real context.When storage costs are growing, compliance requires data retention policies, or users need a right-to-erasure implementation.
The right to erasure under GDPR applies to every system that holds the data — a thorough data map is the prerequisite to any erasure implementation.
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