# Data retention · Glossary
The rules that define how long each type of data is kept, where it is stored during that period and how it is deleted or archived afterwards.
[Glossary](/glossary) · Data governance and quality

# Data retention

     The rules that define how long each type of data is kept, where it is stored during that period and how it is deleted or archived afterwards. Retention periods are set by legal obligations, contractual commitments and genuine business need.

## Why it matters

     Keeping data indefinitely increases storage cost, breach impact and regulatory exposure. Under UK GDPR, personal data should not be kept longer than necessary for the purposes it was collected for, and organisations need to be able to justify their retention periods.

     Retention also matters for AI. Training data, prompts, model outputs and logs are all data with retention implications, and deleting a record from a source system does not remove it from derived datasets unless pipelines are designed to propagate deletion.

## In practice

     For example, a UK recruitment platform might keep unsuccessful candidate records for a defined period after a campaign closes, then delete them automatically from the application database, the warehouse and any analytics extracts, with a log showing the deletion ran.

## Where Rodan fits

     Rodan designs retention and deletion into the data platforms and [Governed Workflow Platforms](https://rodan.io/what-we-build/governed-workflow-platforms) it builds. Lifecycle is one of the six domains in the [Data Governance Toolkit](/governance).

## Related terms

- [Data minimisation](/glossary/data-minimisation)

- [Data governance](/glossary/data-governance)

- [Audit trail](/glossary/audit-trail)

- [Personally identifiable information (PII)](/glossary/personally-identifiable-information)

- [Agent memory](/glossary/agent-memory)
HTML: https://rodan.io/glossary/data-retention