DatriseAI-first ETL

Azure Table Storage Yellowfin

AI-first ETL from Azure Table Storage into Yellowfin. Governed entities, incremental sync, typed landing tables.

How Datrise loads Azure Table Storage into Yellowfin

Datrise syncs Azure Table Storage'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

Azure Table Storage: SaaS or API data source for analytics and warehouse sync.

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

How Azure Table Storage entities map to Yellowfin

Azure Table Storage entityYellowfin objectNotes
recordsazure_table_storage_recordsid PK · custom fields → flattened columns
eventsazure_table_storage_eventsdate/time dimensions events
configuration objectsazure_table_storage_configuration_objectsid PK · linked to azure_table_storage_records

FAQ

How does Datrise handle Azure Table Storage'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 Azure Table Storage 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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