Dataset Historization: Tracking Data Over Time
Dataset Historization automatically saves previous versions of your dataset results each time they refresh. This lets you track how your data changes over time and recover past states.
Step 1: Understand How Historization Works
- Every time a dataset refreshes (manually or on schedule), BEEM stores a snapshot of the results
- Each snapshot is timestamped and linked to the query version that produced it
- This happens automatically for all deployed datasets — no additional setup required
- Navigate to the Warehouse in the left sidebar
- Open the dataset you want to inspect
- Look at the version history panel
- Each entry shows: the deployment timestamp, the query version (DEPLOYED, UNDEPLOYED, FAILED, EDITED), who made the change
- Open the dataset version history
- Find the version you want to restore
- Click Roll Back to revert the SQL query to that version
- The platform redeploys the previous query
- The next refresh produces results based on the restored version
- Open the Monitor in the left sidebar to see execution history
- Cross-reference dataset refresh events with version history
- Use this for compliance reporting and change tracking
- Regulatory compliance: Prove what data looked like at a specific point in time
- Debugging: Compare current results to a previous version to find what changed
- Recovery: Roll back to a known-good state if a query change introduces errors
- Trend analysis: Track how metrics evolve over successive refreshes
- Historization is included in all pricing tiers (Essentials, Pro, Enterprise)
- Snapshots are stored in your dedicated cloud warehouse
- Storage consumed by historical snapshots counts toward your storage allocation
- Query version control and historization work together: you control the SQL, BEEM preserves the output history