DatriseAI-first ETL

Smaily MicroStrategy

AI-first ETL from Smaily into MicroStrategy. Governed entities, incremental sync, typed landing tables.

How Datrise loads Smaily into MicroStrategy

Datrise syncs Smaily'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

Smaily: SaaS or API data source for analytics and warehouse sync.

MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.

How Smaily entities map to MicroStrategy

Smaily entityMicroStrategy objectNotes
recordssmaily_recordsid PK · custom fields → flattened columns
eventssmaily_eventsdate/time dimensions events
configuration objectssmaily_configuration_objectsid PK · linked to smaily_records

FAQ

How does Datrise handle Smaily'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 Smaily to MicroStrategy sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.

Related pipelines

Early access

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