Can people rely on this information?
A sales report can be wrong if orders are missing, counted twice, or arrive after the report is made. These are data quality problems. A rough count may be enough to spot a trend, but billing needs the right customer and exact amount.
Teams check for missing details, repeated records, and late arrivals. A data pipeline can run these checks as records move from an app into reports.
Fix the source of the error
Correcting one spreadsheet may make today’s chart look right, but the error will return if the original records remain wrong. Teams trace the problem to its source, decide who will fix it, and make failed checks visible.