DatriseAI-first ETL

Excel File to Looker Studio Integration

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

How Datrise loads Excel File into Looker Studio

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Excel File entities map to Looker Studio

Excel File entityLooker Studio objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → flattened columns for chart fields
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 Looker Studio?

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

How does the Excel File to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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