A local business dataset usually starts as a list scraped or exported from a directory, and usually has the same problems: inconsistent category names, missing phone numbers, and addresses formatted five different ways.

Start with a fixed schema: business name, full address, phone, website, a category drawn from a controlled list (not free text), and a review count or rating captured with a timestamp since that number changes constantly.

Normalize before you publish. Pick one address format, one phone format, and a single category taxonomy, then map every record into it. This is the step that turns a scraped list into something an agency or lead-gen team can actually filter and use.

Document your capture date. Business data goes stale -- phone numbers change, businesses close. A dataset with a clear "as of" date is more trustworthy than one that implies it's always current.