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Quality dashboard & corrections

Executing your rules measures the quality of your data, and those measurements feed a data-quality dashboard.

What the dashboard shows​

The dashboard gives both an overview and a per-dimension breakdown, including:

  • Volumes — number of datasets, cells, rows, and rules
  • Distribution — cells per table, rows per dataset, and how rules are spread across datasets
  • Global data-quality score — a single headline percentage
  • Score per dimension — a radar view across Completeness, Accuracy, Consistency, Validity, Timeliness, and Uniqueness

This makes it easy to see, at a glance, where quality is strong and where it needs attention.

From measurement to correction​

Reviewing the dashboard lets you detect quality anomalies and then run correction processes, which can be automatic or manual. Corrections may be applied either:

  • at the source of the data, or
  • in your decision-support / BI layer

A continuous practice​

Measuring quality and correcting data is not a one-off task. It must be done continuously so your organization can reach and maintain a level of quality that supports reliable data exploitation and sound decision-making.