Why scanned tables are harder to extract
A scanned PDF is often just an image of a table. The rows, columns and values are visible to a person, but there may be no selectable text or spreadsheet structure inside the file.
OCR first has to recognise the characters. The extraction workflow then has to infer which recognised values belong together as rows and columns.
Use OCR on image-only pages
For scanned documents, use a workflow with OCR support or create a searchable PDF first. Check names, dates and numeric values in the OCR result because recognition errors can become spreadsheet errors later.
Blur, skew, shadows, low contrast and compression damage can reduce OCR accuracy. Clean scans usually produce more reliable table extraction than camera photos or heavily degraded pages.
Reconstruct the table after text recognition
Once text is available, the extractor uses page layout and detected positions to organise values into structured rows and columns.
Ruled tables are often easier to interpret than loose multi-column layouts, but merged headers, wrapped descriptions and multi-line cells can still need manual correction.
Review before exporting to Excel or CSV
Inspect the extracted table before download. Pay particular attention to decimal points, negative signs, dates, totals and values that are visually close together in the scan.
Correct any cells that need adjustment, then export the reviewed result to the spreadsheet format supported by your workflow.
Do not treat OCR output as verified financial data
A single recognition mistake can change a number significantly. If the spreadsheet will be used for accounting, financial analysis, compliance or reporting, compare the important values against the original scan.
Keep the original PDF unchanged and use the extracted spreadsheet as a working copy rather than as the only record.