Checks Introduction¶
Understanding checks
A check turns an expectation about your data into a result Qualytics can evaluate: a rule type applied to a table or a file, run by every Scan, with each failure reported as an anomaly. This deep dive is the reference for the concepts every check shares, whatever its rule type. Each rule type has its own section under Rule Types.
Why Use Checks¶
Checks are how a data quality program writes down what "correct" means, so it can be tested every time the data changes.
Use checks to:
- Catch bad data early: Every Scan tests new data against your rules, so a broken load or an unexpected value shows up as an anomaly before anyone builds on it.
- Write down business rules: Authored checks hold the limits, references, and relationships your team knows to be true, and automation never changes them.
- Start from what the data already does: AI Managed checks give broad coverage from observed patterns, with no rule written by hand.
- Focus on what matters: Importance and impact metrics decide how loudly each failure speaks during triage.
- Test before you trust: Validate and Dry Run show what a check will flag before a Scan relies on it.
- Keep a record: Every change to a check, and the discussion behind it, stays on its Timeline.
What You Will Find Here¶
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How a Check Works
What a check is made of, who creates it, how AI Managed checks are generated, how a Scan evaluates it, and how its status changes.
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Authored Checks
What an Authored check is, who governs it, and how it differs from an AI Managed check.
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AI Managed Checks
What an AI Managed check is, which edits convert it to Authored, and how to go back.
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Check Ownership
Who is responsible for a check, the four ways ownership changes, notifications, and filtering by owner.
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Check Importance
How much a check's failures matter, and how its tags raise or lower it.
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Impact Metrics
Numbers measured over a check's failed records that show how big a failure is.
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Dry Run
What a Dry Run evaluates and how to read its results, anomalies, and source records.
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Check Views
The check lists, the check page, and the side panel: how to reach each one, what it shows, and what you can do there.
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Check Anomalies
The anomalies a check has produced, and how to triage them from the check's page.
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Check Timeline
The change log of a check, its past versions, and the comments your team leaves on it.
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Check Examples
Scenarios that show ownership and AI Managed checks in practice.
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Check Permissions
Which team permissions can view, create, edit, archive, and delete checks, change owners, and edit AI Managed checks.
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Getting Started with Checks
Every rule type, in the same groups as the rule type picker, with a link to its own reference, examples, how-tos, and API.