Best practice 3.7 – Implement data retention policies for each class of data in the analytics workload
The business’s data classification policies determine how long the analytics workload should retain the data and how long backups should be kept. These policies help ensure that every system follows the data security rules and compliance requirements. The analytics workload should implement data retention and backup policies according to these data classification policies. For example, if the policy requires every system to retain the operational data for five years, the analytics systems should implement rules to keep the in-scoped data for five years. More information on data retention can be found in Sustainability .
Suggestion 3.7.1 – Create backup requirements and policies based on data classifications
Data backup should be based on business requirements, such as recovery point objective (RPO), recovery time objective (RTO), data classifications, and the compliance and audit requirements.
Suggestion 3.7.2 – Create data retention requirement policies based on the data classifications
Avoid creating blanket retention policies. Instead, policies should be tailored to individual data assets based on their retention requirements.
For more details, refer to the following information:
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AWS Big Data Blog: Building a cost efficient, petabyte-scale lake house with Amazon S3 Lifecycle rules
and Amazon Redshift Spectrum: Part 1 -
AWS Big Data Blog: Retaining data streams up to one year with Amazon Kinesis Data Streams
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AWS Big Data Blog: Retain more for less with UltraWarm for Amazon OpenSearch Service
Suggestion 3.7.3 – Create data version requirements and policies
Implement a process that captures the data version to address, based on compliance, security, and operational requirements.
For more details, refer to the following information:
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AWS Storage Blog: Reduce storage costs with fewer noncurrent versions using Amazon S3 Lifecycle
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AWS Storage Blog: Simplify your data lifecycle by using object tags with Amazon S3 Lifecycle
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AWS Database Blog: Implementing version control using Amazon DynamoDB
