DatriseAI-first ETL

Excel File to Sisense Integration

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

How Datrise loads Excel File into Sisense

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

Sisense: Analytics platform with elastic data models and embedded analytics.

How Excel File entities map to Sisense

Excel File entitySisense objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → flattened columns for the cube
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 Sisense?

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

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

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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