Excel to CSV strips a spreadsheet down to its raw data — no fonts, no colors, no formulas, no charts, no merged cells — and writes it as plain comma-separated text, right in your browser with no file ever uploaded and nothing to install. This is the opposite trade-off from converting the other direction: you are deliberately throwing away everything Excel added on top of the numbers, because the destination you're sending the file to (a database import, a script, an API) doesn't understand XLSX and never will. Most data pipelines outside the Microsoft ecosystem — PostgreSQL's COPY command, a Python pandas.read_csv() call, a bulk import screen in Salesforce or Mailchimp — expect flat rows of text, not a ZIP archive of XML parts describing cell styles and worksheet relationships.
The conversion is lossy by design, and understanding what gets dropped matters. Formulas are replaced by their last-calculated result — a cell showing =VLOOKUP(A2,Sheet2!A:B,2,0) becomes whatever value it evaluated to, with no way to recover the formula afterward. Cell formatting (currency symbols, date display formats, bold headers, conditional formatting colors) disappears entirely, since CSV has no concept of cell styling. Multiple worksheets in one workbook don't fit into a single CSV file either, since CSV is a flat, single-table format — a workbook with several tabs produces several separate CSV files, one per sheet.
This matters most to people building or feeding systems rather than just reading data: developers writing an import script, analysts loading a dataset into R or a BI tool, and ops teams pushing spreadsheet-based lead lists into a CRM that only accepts CSV uploads.
Have an older .xls file first? XLS to XLSX upgrades it to the modern format before you extract the CSV.
