Streak → MicroStrategy
AI-first ETL from Streak into MicroStrategy. Governed entities, incremental sync, typed landing tables.
How Datrise loads Streak into MicroStrategy
Datrise syncs Streak's contacts, accounts, deals, activities, and lifecycle events 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
Streak: CRM for SMB teams managing pipeline, contacts, and customer activity.
MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.
How Streak entities map to MicroStrategy
| Streak entity | MicroStrategy object | Notes |
|---|---|---|
| contacts | streak_contacts | id PK · custom fields → flattened columns |
| accounts | streak_accounts | id PK · linked to streak_contacts |
| deals | streak_deals | id PK · linked to streak_contacts |
| activities | streak_activities | date/time dimensions events |
FAQ
How does Datrise handle Streak'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 Streak 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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