ConsoliSheetStandardising column names is not the same job as matching them. Matching decides that two spreadsheets are talking about the same field; standardising decides what to call it once everyone agrees.
Formatting differences
Examples“customer name ” vs “Customer Name”; trailing spaces; inconsistent capitalisation.
RuleNormalise automatically. No business meaning is at stake.
Plausible aliases
Examples“Client”, “Customer Name” and “Company” likely meaning the same field.
RuleConfirm once, then save the alias for reuse on future files.
Different fields
Examples“Account” (a number) vs “Account Name”; “Net Cost” vs “List Price”.
RuleA similarity score is not proof of identical meaning.
Normalisation and mapping are different jobs
Turning “Customer Name ” into “customer name” is normalisation: mechanical, reversible, safe to automate completely. Deciding that “Client” and “Customer Name” refer to the same underlying field is mapping: a judgement call about business meaning, and judgement calls deserve a human the first time they come up.
Save the decision, not just the answer
Once you have confirmed that “Client” means Customer, that mapping should not need re-confirming every month. Recurring reporting is exactly where saved, approved aliases turn a repeated manual decision into configuration you set once.
Common questions
Should similar-looking headers be merged automatically?
Only when the similarity is purely formatting. Business-term differences deserve a one-off human check, not an automatic guess.
What is a target schema?
The agreed structure of your final dataset: the field names you want, and what each one is supposed to mean.
Building a standard column list?
ConsoliSheet proposes matches against your target columns and stops for confirmation whenever a mapping is genuinely ambiguous, rather than merging silently.
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