DatriseAI-first ETL

FullStory MicroStrategy

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

How Datrise loads FullStory into MicroStrategy

Datrise syncs FullStory's sessions, events, funnels, frustration signals, and user properties 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

FullStory: Digital experience analytics with session replay context.

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

How FullStory entities map to MicroStrategy

FullStory entityMicroStrategy objectNotes
sessionsfullstory_sessionsid PK · custom fields → flattened columns
eventsfullstory_eventsdate/time dimensions events
funnelsfullstory_funnelsid PK · linked to fullstory_sessions
frustration signalsfullstory_frustration_signalsid PK · linked to fullstory_sessions

FAQ

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

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

Related pipelines

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