DatriseAI-first ETL

AWS CloudTrail to MicroStrategy Integration

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

How Datrise loads AWS CloudTrail into MicroStrategy

Datrise syncs AWS CloudTrail's API events, identities, resources, event sources, error codes, and request parameters 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

AWS CloudTrail: AWS account activity and API audit logging.

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

How AWS CloudTrail entities map to MicroStrategy

AWS CloudTrail entityMicroStrategy objectNotes
API eventsaws_cloudtrail_api_eventsdate/time dimensions events
identitiesaws_cloudtrail_identitiesid PK · linked to aws_cloudtrail_api_events
resourcesaws_cloudtrail_resourcesid PK · linked to aws_cloudtrail_api_events
event sourcesaws_cloudtrail_event_sourcesdate/time dimensions events

FAQ

How does Datrise handle AWS CloudTrail'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 AWS CloudTrail 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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