Glossary

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Glossary / Evaluation and implementation guide

Data Retention Policy

A data retention policy specifies how long each class of data is kept, where it lives during that period, and how it is deleted or anonymized at the end.

In vendor evaluations it translates into concrete requirements: event-level expiry, backup coverage, and provable deletion across primary stores, replicas, and downstream copies.

A practical example

Example: a policy states that raw clickstream events expire after 18 months, aggregated reports persist indefinitely, and deletion requests propagate to the warehouse and connected marketing tools within 30 days.

What to evaluate before investing

  • Ask whether retention can be configured per table or event type, not only globally
  • Verify deletion covers backups, replicas, and exports, and request documentation of the process
  • Check if the platform supports legal-hold exceptions without breaking the standard schedule

Limitations and tradeoffs

Strict retention reduces the historical depth available for trend analysis and model training, so teams must balance compliance windows against analytical needs.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.