DatriseAI-first ETL

Excel File to Databricks SQL Warehouse Integration

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

How Datrise loads Excel File into Databricks SQL Warehouse

Datrise syncs Excel File's worksheets, rows, columns, headers, cell ranges, and workbooks into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Excel File: Spreadsheet workbooks from exports and shared drives.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Excel File entities map to Databricks SQL Warehouse

Excel File entityDatabricks SQL Warehouse objectNotes
worksheetsexcel_file_worksheetsid PK · custom fields → VARIANT or STRUCT columns
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 Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Excel File to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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