DatriseAI-first ETL

Excel File to CSV Files Integration

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

How Datrise loads Excel File into CSV Files

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Excel File entities map to CSV Files

Excel File entityCSV Files objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → JSON-encoded strings for nested 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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the Excel File to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

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