Getting Started with Datastore Quality Score
Data Quality Scores give you a quantified, at-a-glance measure (0–100) of how healthy your data is across every datastore, container, and field in Qualytics. Scores are calculated automatically after every Profile and Scan operation, recorded as time series, and composed of 8 quality dimensions — so you can track improvements, prioritize remediation, and report on data governance.
In this section you will learn how scores are calculated, how to configure scoring settings, and how to use scores to monitor data quality. Any user with the Member role can view scores; editing score settings requires the Editor team permission.
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Introduction
Learn how quality scores are calculated, the score hierarchy (field → container → datastore), the 8 dimensions, and what triggers recalculations.
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Permissions
See which roles can view quality scores and edit scoring settings.
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Settings
Configure the decay period and dimension weights for a datastore.
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Weighting
Understand how rule type, anomaly, and tag weights combine to determine check importance.
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API
Retrieve and update quality score settings and access historical score data via the API.
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FAQ
Troubleshooting, decay period behavior, dimension weights, independent settings, recalculations, and more.