DatriseAI-first ETL

Azure Table Storage to Tableau Integration

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

How Datrise loads Azure Table Storage into Tableau

Datrise syncs Azure Table Storage's tables, entities, partition keys, row keys, properties, and timestamps 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 Table Storage: Key-value NoSQL store on Azure.

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

How Azure Table Storage entities map to Tableau

Azure Table Storage entityTableau objectNotes
tablesazure_table_storage_tablesid PK · custom fields → flattened columns for Tableau fields
entitiesazure_table_storage_entitiesid PK · linked to azure_table_storage_tables
partition keysazure_table_storage_partition_keysid PK · linked to azure_table_storage_tables
row keysazure_table_storage_row_keysid PK · linked to azure_table_storage_tables

FAQ

How does Datrise handle Azure Table 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 Table 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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