DatriseAI-first ETL

Microsoft SQL Server to Tableau Integration

AI-first ETL from Microsoft SQL Server into Tableau. Governed entities, incremental sync, typed landing tables.

How Datrise loads Microsoft SQL Server into Tableau

Datrise syncs Microsoft SQL Server's tables, rows, schemas, indexes, primary keys, and change tracking 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

Microsoft SQL Server: Microsoft SQL Server transactional databases.

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

How Microsoft SQL Server entities map to Tableau

Microsoft SQL Server entityTableau objectNotes
tablesmssql_sql_server_tablesid PK · custom fields → flattened columns for Tableau fields
rowsmssql_sql_server_rowsid PK · linked to mssql_sql_server_tables
schemasmssql_sql_server_schemasid PK · linked to mssql_sql_server_tables
indexesmssql_sql_server_indexesid PK · linked to mssql_sql_server_tables

FAQ

How does Datrise handle Microsoft SQL Server'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 Microsoft SQL Server 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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