DatriseAI-first ETL

Aws Cloudtrail Yellowfin

AI-first ETL from Aws Cloudtrail into Yellowfin. Governed entities, incremental sync, typed landing tables.

How Datrise loads Aws Cloudtrail into Yellowfin

Datrise syncs Aws Cloudtrail's records, events, and configuration objects into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

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

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Aws Cloudtrail entities map to Yellowfin

Aws Cloudtrail entityYellowfin objectNotes
recordsaws_cloudtrail_recordsid PK · custom fields → flattened columns
eventsaws_cloudtrail_eventsdate/time dimensions events
configuration objectsaws_cloudtrail_configuration_objectsid PK · linked to aws_cloudtrail_records

FAQ

How does Datrise handle Aws Cloudtrail's custom fields in Yellowfin?

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 Yellowfin types.

How does the Aws Cloudtrail to Yellowfin sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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