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Anomaly Details

  • The Anomaly Details modal provides specific details about the Anomaly, including source record and checks that failed assertions, along with ability to take Notes and provide feedback to ML methods through updating Status of the anomaly.

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  • Users have the ability to provide feedback to the ML methods through Supervised Learning. Specifically, the user can Acknowledge, Resolve or Invalidate an anomaly. Each of these actions will change the tolerances of the data quality checks behind the anomaly.

  • Datastore details: Screenshot Screenshot

    1. The # ID of the anomaly: 69962
    2. The Datastore name: AzureSQL - Consolidated Balance
    3. The Location where this data is stored:
    4. The Record Type of the anomaly: Shape
    5. The Tags are labels that serve the purpose of grouping anomalies and driving downstream workflows: High
    6. The Status of the selected Anomaly: Users can edit the status to Acknowledged, Resolved or Invalid.
    7. The Detected at of the anomaly creation time: 02/21/23 5:40 PM
  • Failed Fields details: Screenshot Screenshot

    • Field: all the fields of that specific anomaly found: currency

    • Rule: rule type that failed the assertion(s) You can check all the Rule types here.

    • Violation: details of how the anomaly failed the assertion(s) of rule(s)

    • Coverage Screenshot: the expected tolerance of the rule

    • Type Screenshot: Infered or Authored

    • The rule type Tag

  • Source Records:

    Show in a tabular view all the records and fields and highlight records with anomaly data based on the rule type

    Screenshot Screenshot Users can filter by Field in this view

Infered check details

  • Clicking into a Rule will highlight its details and enables users to edit the rule as well:

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  • An anomaly can be archived via the Screenshot button.

  • If you expand the section Advanced Options you can add a Filter clause and also change the Coverage percentage for that anomaly.


The Filter clause is a WHERE statement against your table. For example:
price != 33 or price > discount + 20


You can create a computed table and use multiple fields from different tables in a filter clause

Suggested remediation

Qualytics can also provide you a suggested value

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Last update: December 1, 2023