DatriseAI-first ETL

AWS CloudTrail to Tableau Integration

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

How Datrise loads AWS CloudTrail into Tableau

Datrise syncs AWS CloudTrail's API events, identities, resources, event sources, error codes, and request parameters into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

AWS CloudTrail: AWS account activity and API audit logging.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How AWS CloudTrail entities map to Tableau

AWS CloudTrail entityTableau objectNotes
API eventsaws_cloudtrail_api_eventsdate/datetime fields 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/datetime fields events

FAQ

How does Datrise handle AWS CloudTrail's custom fields in Tableau?

Flexible values are stored as flattened columns for Tableau fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Tableau types.

How does the AWS CloudTrail to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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