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Connect DataFiles & Apps

Excel Upload

You connect Excel Upload from the DataSquares connection wizard. Upload a .xlsx workbook — every visible sheet is imported as a table.

  1. In DataSquares, open Data Sources and choose Connect Source. The Connect a data source page opens.

  2. Pick Excel Upload on that page (search or browse by category).

  3. Name the source, choose the file, then choose Upload & Create.

Pick Excel Upload on the Connect a data source page and upload your file — no credentials needed. Every sheet in the workbook is imported as its own table.

  • Every visible sheet with data becomes a table, named after the sheet. Hidden and very-hidden sheets (lookups, scratch data, a macro’s data) are not imported — unhide a sheet in Excel and upload again to include it.
  • The header is the first row that looks like one: title lines and blank rows above it are skipped, and unnamed header cells get positional names.
  • Column types are inferred from the cells: numbers stay numbers, date cells become dates (a cell with no time of day becomes a calendar date), booleans become booleans.
  • Numbers stored as text in the workbook (1.234,50, €12) import as text unless you choose Numbers in this file — 1,234.56 or 1.234,56 — when you upload (API: numberFormat=dot|comma). Cells Excel already holds as numbers are always read as they are.
  • Formulas import as their computed values — formula logic doesn’t execute after import.
  • .xlsx and .xlsm (macros are ignored). Re-save legacy .xls files as .xlsx; a CSV renamed to .xlsx is imported as CSV.
  • Workbooks are read row by row, so large files import without loading the whole workbook into memory. A sheet can have at most 1,600 columns.

The importer wants each sheet to be a plain grid: a header row, one record per row. Merged cells and pivot-style layouts import poorly — flatten them first.

Open the source’s Replace file action and upload the new workbook. It is read exactly like the original and swapped in under the same source, so the models and dashboards built on it keep working and show the new data. Sheets or columns missing from the new file disappear from the staged tables; every replacement is listed in the source’s run history.

Uploads and replacements are imported in the background, with progress and Cancel in the app — see CSV: importing in the background.