Inspect the structure of your table
Upload a supported Excel file and review the parsed columns and inferred types. Confirm that the data preview matches the table you intended to analyze, particularly when the source workbook has title rows or formatting around the data.
Find gaps and unusual values
Column-level profiles show missing values and summary statistics. Use distributions and outlier information to investigate entries that may need correction. An unusual value can be a real observation, so compare it with the source before removing it.
Example: prepare a monthly sales table
Check that dates, amounts, and region labels have sensible types. Inspect missing amounts and unusually large values, then compare distributions before choosing cleaning operations. This workflow helps you decide which issues matter for a report instead of changing every flagged value automatically.
Know what profiling can tell you
Data profiling describes the parsed dataset; it is not a full audit of workbook formulas, macros, or formatting. Confirm the imported data and keep your original workbook so that you can trace any changes back to their source.
How to get started
- Upload your Excel table and confirm the imported preview.
- Review missing fields, data types, and statistical summaries.
- Choose cleaning operations and export the prepared data.