DatriseAI-first ETL

Excel File to Spotfire Integration

AI-first ETL from Excel File into Spotfire. Governed entities, incremental sync, typed landing tables.

How Datrise loads Excel File into Spotfire

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Excel File entities map to Spotfire

Excel File entitySpotfire objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → flattened columns for visualizations
rowsexcel_file_rowsid PK · linked to excel_file_worksheets
columnsexcel_file_columnsid PK · linked to excel_file_worksheets
headersexcel_file_headersid PK · linked to excel_file_worksheets

FAQ

How does Datrise handle Excel File's custom fields in Spotfire?

Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.

How does the Excel File to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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