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To find who changed a record, the platform must have audit history enabled for the relevant data, and your account must have permission to view it. A useful audit trail identifies the record, the person or account responsible, the time and operation, and—when field-level auditing is configured—the changed field and its old and new values. Microsoft Dataverse documents these capabilities, along with limits that make it unsafe to assume every change is recorded or kept indefinitely.
What an audit trail can tell you
An audit trail is more than a record’s “last modified” date. Depending on the platform and its configuration, it can answer who created, updated, or deleted a record, when the operation happened, which fields changed, and what values they held before and after.
Dataverse’s audit table includes the operation, the audited record, the user who changed the data, and the time associated with the operation. Its change details can include old and new values. Microsoft says that in July 2025 it enhanced the accuracy of the CreatedOn timestamp to include milliseconds, helping distinguish the sequence of multiple operations in a transaction. Microsoft describes the audit table as read-only.
Auditing can also cover record sharing, many-to-many associations and disassociations, security-role changes, and user access logging. Which events are available depends on the audit settings and the particular view or retrieval method.
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How to check a record’s audit history in Dataverse
Inspect a record in a model-driven app
- Confirm the audit settings. Check that auditing is enabled for the environment, the table, and the relevant columns. Organization-level auditing alone does not ensure that every table or field has the history you need.
- Open the record’s history. In the model-driven app, select the record and choose Related > Audit History. Your account needs the View Audit History privilege.
- Filter for the field or event. Use the history view’s field filter to narrow the entries. For an update, Dataverse creates an audit record when the new column value differs from the old value.
- Allow for logging delay. Audit entries may not appear immediately because they are stored in log storage.
Review activity across the environment
The environment-wide Audit Summary view requires the View Audit Summary privilege. It is distinct from access to an individual record’s audit history, so grant the privilege that matches the user’s task rather than assuming one permission covers both views.
Retrieve audit details programmatically
Dataverse supports retrieval through the Web API and .NET SDK. There is an important difference in the detail response: the Web API’s AuditDetail derived types do not return the inherited AuditRecord navigation property that carries actor and time information. Microsoft’s .NET SDK sample obtains those details from the audit record. If an application needs to show who acted and when, verify that its retrieval path supplies that metadata instead of assuming the detail payload does.
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Microsoft’s administration documentation says audit-log export through the interface is not currently supported; it directs users to the Web API or .NET SDK for retrieval.
Why a change may be missing or incomplete
- Auditing was not enabled at the needed scope. Verify the environment setting and the specific table and columns. If a field was not audited, its expected field-level history may not exist.
- The viewer lacks a privilege. Check for View Audit History for record history or View Audit Summary for the environment-wide summary.
- The entry has not appeared yet. Dataverse audit views can show logs with a delay.
- The history was removed or aged out. Audit logs consume log storage capacity. Dataverse has an environment setting for the number of days to retain logs, and administrators can delete audit history by record or by table, access log, or date. Once the relevant history is deleted, it is no longer available for investigation.
- A large value was truncated. Microsoft says certain large attribute values are capped at 5 KB or about 5,000 characters; an ellipsis indicates truncation. The truncated value cannot be used to restore the full original value.
- The API response does not include actor and time. A Web API change-detail response may not contain the audit record property that carries those fields. Check the response shape or use an SDK approach that retrieves the audit record.
What to verify before relying on audit history
Audit history is a configured record of activity, not a universal guarantee that every platform captures every change forever. Before using it for an investigation or governance requirement, verify the behavior in the specific product and environment:
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- Which events are captured: record creation and updates, deletion, sharing, access, or configuration changes.
- Whether auditing must be enabled, and whether it can be scoped to an environment, table, or field.
- Whether the history records the actor, time, operation, changed fields, and old and new values you need.
- Which roles can view the history and how an authorized administrator can retrieve it.
- How long entries are retained, how storage is managed, and who can delete logs.
- Whether large values are truncated or API responses omit information shown in the interface.
For a limited cross-platform example, Salesforce’s official Security Guide search result says that, without Field Audit Trail, field history is retained for up to 18 months, or up to 24 months through the API. It also says fields longer than 255 characters are recorded as edited without old and new values. Those are Salesforce-specific statements, not a standard for low-code platforms generally.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Set up a trail that answers the real question
- Identify the fields and events that matter. Prioritize business-critical or regulated data, and decide whether you need evidence of edits only or also deletions, sharing, and access.
- Enable auditing at each required scope. In Dataverse, check organization, table, and relevant column settings.
- Grant history access carefully. Assign audit-view privileges only to people who need them.
- Validate with a test change. In your own environment, change a field and confirm that the history shows the expected actor, time, operation, and before-and-after values.
- Set retention and deletion rules. Match the environment’s retention configuration and log-storage capacity to your operational and compliance needs. Decide who can delete history and how such deletions are governed.
- Test the actual retrieval route. If an application or process depends on an API or SDK, confirm that it returns the identity, timestamp, and field details your investigation requires.
Dataverse is a documented example, not proof that every low-code platform has the same settings or coverage. Check the product’s own documentation and your environment’s configuration before treating an audit trail as evidence.
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