Azure Blob Storage to Yellowfin Integration

How Datrise loads Azure Blob Storage into Yellowfin

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions 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 Blob Storage: Object storage for blobs and data lake files on Azure.

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

How Azure Blob Storage entities map to Yellowfin

Azure Blob Storage entity	Yellowfin object	Notes
containers	`azureblobstorage_containers`	id PK · custom fields → flattened columns
blobs	`azureblobstorage_blobs`	id PK · linked to azureblobstorage_containers
blob metadata	`azureblobstorage_blob_metadata`	id PK · linked to azureblobstorage_containers
snapshots	`azureblobstorage_snapshots`	id PK · linked to azureblobstorage_containers

FAQ

How does Datrise handle Azure Blob 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 Blob Storage to Yellowfin sync stay up to date?

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

Related pipelines

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