Reports, dashboards and AI models all depend on the quality of the data that feeds them. Poor data quality leads to wrong conclusions and lost confidence.
Common data problems
- Missing values and incomplete records
- Duplicates created by multiple systems
- Inconsistent formats for names, phone numbers and dates
- Outdated information that was never updated
Prevent problems at the source
Validation rules in forms and applications stop bad data from entering systems in the first place.
Assign ownership
Every important dataset should have an owner responsible for its accuracy and definitions.
Monitor continuously
Automated checks can flag unusual values or sudden changes before they reach decision makers.
Improving data quality is rarely glamorous, but it is one of the highest-value investments an organisation can make.
Need help putting this into practice?
Our team at Ingata Technologies can help you plan, build and support the right solution for your organisation.
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