Data State
Data State in Salesforce is the lifecycle classification assigned to a field through the Data Classification framework, indicating whether the data in the field is currently Active (in production use), Archived (retained but not actively used), or Purged (deleted or scheduled for deletion).
Definition
Data State in Salesforce is the lifecycle classification assigned to a field through the Data Classification framework, indicating whether the data in the field is currently Active (in production use), Archived (retained but not actively used), or Purged (deleted or scheduled for deletion). The classification helps the platform and downstream compliance tooling reason about which data is operationally live, which is retained for compliance only, and which has aged out of retention. Admins set Data State per field as part of the broader Data Classification metadata alongside Sensitivity Level and Compliance Categorization.
Data State exists because privacy and retention regulations distinguish between operational data the org actively uses and historical data the org keeps only because regulation requires retention. Treating the two the same overstates the org's data footprint and complicates DSR scoping. The Data State classification gives admins a structured way to declare the lifecycle status of each field, which downstream compliance and data governance tools can consume to scope reports, retention automation, and access controls.
Why Data State adds a lifecycle dimension to the broader Data Classification framework
Where Data State lives in setup
Data State is a dimension within Data Classification, configured per field through Object Manager, Field, Data Classification section. The dimension is enabled org-wide through Setup, Data Classification Settings. Standard values are Active, Archived, and Purged; admins can customize the value set per the org's data lifecycle policy. The classification value writes to field metadata alongside Sensitivity Level, Compliance Categorization, and Data Owner; together they form the field's classification profile.
The three standard Data State values
Active means the field is in current production use; the data drives workflows, automation, reports. Archived means the field still holds data but is no longer actively used; retention or historical reporting is the only justification for keeping it populated. Purged means the field has been cleared or scheduled for clearing; the data is gone or going. The values guide compliance reporting (Active PII fields need access control; Purged PII fields do not), retention automation (Archived fields are candidates for delete-after-retention), and data inventory scoping (DSRs scope to Active fields by default).
Data State in DSR (Data Subject Request) workflows
DSR workflows scope which fields to include in a data export or delete based on classification. Active fields always include; Archived fields include subject to policy; Purged fields are skipped. The Data State value lets the DSR workflow distinguish operational data from historical retention without manual per-field review. Most regulated orgs configure DSR workflows to honor Data State automatically; without the classification, DSR scoping is manual and error-prone.
Retention automation and the Archived state
Fields classified Archived are candidates for retention automation. A scheduled Flow or Apex job that runs monthly can identify records older than the retention window and clear the Archived fields on those records, leaving Active fields populated. The pattern preserves operational data while honoring the retention policy on the Archived data. Without the Data State classification, the retention job has no way to know which fields to clear; the classification is the upstream decision.
Compliance reporting and the Active-only filter
Compliance reports often need to count Active PII fields rather than every PII field ever defined. A field marked Compliance Categorization = PII plus Data State = Active is in scope; PII + Archived may be in scope per policy; PII + Purged is not. The Data State dimension filters the compliance inventory to operational reality. Most regulator questions are about Active data; the inventory should reflect what is actually live, not the historical accumulation.
Maintenance and the lifecycle transition
Fields move through lifecycle states as the org evolves. A field that was Active in 2024 may become Archived in 2026 as the workflow it served is retired. A field that was Archived in 2025 may become Purged in 2027 after the retention window elapses. The maintenance discipline: quarterly review of field usage, update Data State as workflows evolve, document transitions. The classification stays useful only when admins update it; static classifications go stale as the org changes.
Custom Data State values and the org-specific lifecycle
The Active/Archived/Purged trichotomy works for most orgs. Some orgs need finer granularity: Pending (the field is configured but no data flows yet), Deprecating (the field is in transition out of use), Legal Hold (the field is preserved for litigation regardless of retention policy). Salesforce supports customizing the Data State value set per the org's data lifecycle. The customization adds value when downstream tooling respects the additional values; without consumers, custom values are inventory only.
How to use Data State as part of the Data Classification program
The pattern: enable Data State in Data Classification, classify fields per current usage, build downstream consumers (DSR scoping, retention automation, compliance reports) that respect the state, audit quarterly as fields transition. The classification is most valuable when the workflows that consume it exist; configuration alone is inventory.
- Enable Data State in Data Classification Settings
Setup, Data Classification Settings. Confirm Data State is in the enabled dimensions list.
- Decide whether to use standard or customized values
Active/Archived/Purged works for most orgs. Customize only when downstream tooling will consume the additional values.
- Classify existing fields through bulk Download/Upload
Per-field classification is impractical past a few dozen fields. Use the bulk pattern: download, classify in CSV, upload back.
- Build DSR workflow that respects Data State
Privacy Center or custom Flow/Apex. Scope DSR scoping by Data State = Active (or per policy).
- Build retention automation for Archived fields
Scheduled Flow or Apex that clears Archived fields on records past retention window. The automation is the enforcement of the classification.
- Build compliance reports filtered by Data State
Active-only filters answer regulator questions about live data; Archived-included filters answer broader inventory questions.
- Audit field lifecycle quarterly
Workflow changes propagate to fields; the Data State classification needs updates. The quarterly cadence catches transitions before they go stale.
Active, Archived, Purged. The trichotomy that works for most orgs.
Pending, Deprecating, Legal Hold for orgs that need finer lifecycle distinction.
Which Data State values are in scope for DSR exports and deletions.
Scheduled clearing of Archived fields per the retention policy.
Active-only, Active+Archived, all states based on report purpose.
- Static Data State classifications go stale. Workflows change; the classification needs updates or it stops reflecting reality.
- Custom Data State values add value only when downstream tooling consumes them. Custom values without consumers are inventory only.
- Retention automation requires explicit build. The Data State classification is the upstream decision; admins build the clearing logic.
- DSR scoping that ignores Data State includes Archived and Purged fields, producing broader exports than the policy requires.
- Bulk classification via Download/Upload is the only practical path for orgs with hundreds of fields. Per-field assignment does not scale.
Trust & references
Cross-checked against the following references.
- Data Classification referenceSalesforce
- Salesforce security overviewSalesforce
Straight from the source - Salesforce's reference material on Data State.
- Data ClassificationSalesforce Help
- Data Classification SettingsSalesforce Help
- Data Protection and PrivacySalesforce Help
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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