Day.ai to MicroStrategy Integration
AI-first ETL from Day.ai into MicroStrategy. Governed entities, incremental sync, typed landing tables.
How Datrise loads Day.ai into MicroStrategy
Datrise syncs Day.ai's contacts, companies, meetings, opportunities, AI summaries, and relationship signals 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
Day.ai: CRM that builds records from meetings and email automatically.
MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.
How Day.ai entities map to MicroStrategy
| Day.ai entity | MicroStrategy object | Notes |
|---|---|---|
| contacts | day_ai_contacts | id PK · custom fields → flattened columns |
| companies | day_ai_companies | id PK · linked to day_ai_contacts |
| meetings | day_ai_meetings | id PK · linked to day_ai_contacts |
| opportunities | day_ai_opportunities | id PK · linked to day_ai_contacts |
FAQ
How does Datrise handle Day.ai'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 Day.ai 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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