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What is data quality and how can a business improve it?
Data quality is how accurate, complete, consistent, timely and unique your data is. Improve it by fixing problems at the source, validating entries, removing duplicates, standardising formats and adding automated checks that flag anomalies before they reach reports. Perfect data is rarely required, only data fit for the decision.
Cleaning data repeatedly downstream is costly. Better to prevent errors:
- Use required fields and dropdowns in entry systems
- Agree naming and coding standards
- Monitor for missing values, duplicates and sudden volume changes
- Assign someone to resolve issues
Perfect data is not the goal. Aim for data that is good enough for the decisions it supports, and be transparent about known limitations.
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