Snowplow → MicroStrategy
AI-first ETL from Snowplow into MicroStrategy. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowplow into MicroStrategy
Datrise syncs Snowplow's records, events, and configuration objects into MicroStrategy as warehouse tables for MicroStrategy's schema objects. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the warehouse tables behind attributes and metrics, so re-runs update only what changed. Date-partitioned facts. MicroStrategy maps attributes to columns, so Datrise lands stable keys and names so metrics don't break.
Ideal for large-scale enterprise reporting and governance.
Endpoints
Snowplow: SaaS or API data source for analytics and warehouse sync.
MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.
How Snowplow entities map to MicroStrategy
| Snowplow entity | MicroStrategy object | Notes |
|---|---|---|
| records | snowplow_records | id PK · custom fields → flattened columns |
| events | snowplow_events | date/time dimensions events |
| configuration objects | snowplow_configuration_objects | id PK · linked to snowplow_records |
FAQ
How does Datrise handle Snowplow's custom fields in MicroStrategy?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MicroStrategy types.
How does the Snowplow to MicroStrategy sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.
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Early access
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