DatriseAI-first ETL

Azure Blob Storage to Tableau Integration

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

How Datrise loads Azure Blob Storage into Tableau

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions 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

Azure Blob Storage: Object storage for blobs and data lake files on Azure.

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

How Azure Blob Storage entities map to Tableau

Azure Blob Storage entityTableau objectNotes
containersazureblobstorage_containersid PK · custom fields → flattened columns for Tableau fields
blobsazureblobstorage_blobsid PK · linked to azureblobstorage_containers
blob metadataazureblobstorage_blob_metadataid PK · linked to azureblobstorage_containers
snapshotsazureblobstorage_snapshotsid PK · linked to azureblobstorage_containers

FAQ

How does Datrise handle Azure Blob Storage'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 Azure Blob Storage 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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