How does poor transformation affect reporting accuracy?

< 1 min read

Poor transformation introduces wrong aggregations and duplicate records in reports.
Incorrect joins can multiply sales rows and inflate revenue numbers.
Missing filters may include cancelled or test transactions in KPIs.
Wrong date handling shifts data into incorrect months or quarters.
Example: Order date vs invoice date confusion changed monthly revenue trend.
Null handling issues can drop customers from retention calculations.
Different reports show different totals, causing stakeholder confusion.
Business decisions like targets and bonuses may be based on wrong data.
Overall accuracy drops and trust in BI reporting decreases.

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