Snowflake to MicroStrategy Integration
AI-first ETL from Snowflake into MicroStrategy. Governed entities, incremental sync, typed landing tables.
How Datrise loads Snowflake into MicroStrategy
Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses 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
Snowflake: Cloud data platform with separated storage and compute.
MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.
How Snowflake entities map to MicroStrategy
| Snowflake entity | MicroStrategy object | Notes |
|---|---|---|
| databases | snowflake_databases | id PK · custom fields → flattened columns |
| schemas | snowflake_schemas | id PK · linked to snowflake_databases |
| tables | snowflake_tables | id PK · linked to snowflake_databases |
| views | snowflake_views | id PK · linked to snowflake_databases |
FAQ
How does Datrise handle Snowflake'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 Snowflake 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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