5.2.3. Data Governance Strategies (Lifecycles, Residency, Retention)

First Principle: A comprehensive data governance strategy defines clear rules for how data is managed throughout its entire lifecycle, ensuring it is handled securely, compliantly, and cost-effectively.

Good governance is about having clear policies for your data.

• Data Lifecycles:
  • Concept: A policy for managing data from its creation to its eventual archival or deletion.
  • AWS Tool: Amazon S3 Lifecycle policies can be used to automatically transition data to more cost-effective storage classes as it ages (e.g., move data from S3 Standard to S3 Glacier Deep Archive after one year) and to expire (delete) it after a set period.
• Data Residency:
  • Concept: The requirement that certain types of data must be stored and processed within a specific geographical location (e.g., a country or region) to comply with laws like GDPR.
  • AWS Tool: You enforce data residency by choosing the appropriate AWS Region to store your data and run your services. AWS will not move your data out of your chosen region without your permission.
• Data Retention:
  • Concept: A policy that defines how long data must be kept for legal, regulatory, or business reasons.
  • AWS Tool: S3 Object Lock can be used to enforce retention policies in a Write-Once-Read-Many (WORM) model, preventing data from being deleted or modified for a fixed amount of time.

Scenario: A European company needs to process customer data for an AI application. They must ensure the data never leaves the EU and is deleted after five years.

Reflection Question: How would the company use AWS Regions to meet the data residency requirement, and S3 Lifecycle policies to meet the data retention (deletion) requirement?

💡 Tip: A good data governance strategy is planned in advance. It is not something you try to apply retroactively. Use AWS services to automate the enforcement of your policies.