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How do I view details for a validation in Elevate Data Hub?

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Validations are jobs that check data for accuracy, quality, and security against pre-defined rules. You can view details for a validation, including applicable rules, error levels, and affected records. A validation may also be exported for further analysis in external applications.

If you cannot access the areas shown in this article, or complete all the steps, you may not have the necessary permissions.

Open Instance

Open Instance

Click the name of the instance.

Open Validations

Open Validations

In the Instance Navigation menu, click the Validations link.

Open Validation

Open Validation

On the Validations page, click the name of the validation.

View Validation

View Validation

The validation page includes filtering options [1] and a table with overview information about the rules in the validation [2].

To export a CSV of all rule violations, click the Export button [3].

Filter Validations

Filter Validation

You can filter the results that display in the Rules table.

To search for a specific rule or search rule text, enter your query in the Search by Rule field [1].

To search by Domain [2], Entity [3], or Result Status [4], click the corresponding drop-down menu, and select the desired option [5].

To clear all applied filters, click the Clear button [6].

View Rules Table

View Rules Table

The Rules table lists all the rules that apply to the validation. Each row contains details about a rule, including:

  • Rule ID [1]: A string of text and/or numbers that identify a specific rule. When authoring a rule, this is the External ID.
  • Rule Text [2]: A short summary of the rule criteria.
  • Domain [3]: A mutually exclusive group of related data elements that form a category (i.e, student) as defined by the data version.
  • Entity [4]: A mutually exclusive sub-group of related data elements within a domain like a subcategory. For example, enrollment of student domain, as defined by the data version.
  • Result Status [5]: An indicator of issues occurring in the flow of data that impairs the accuracy, quality, and/or security of the data as defined by the validation rules. The error level is determined by each rule.
  • Records [6]: The number of records that triggered an error out of the total number of records applicable to that rule in the validation job.

View Result Status

View Result Status

Errors in data validation are indicated by a severity level, as defined by each rule. Examples of potential error levels include:

  • No Violations [1]: All the data passed with no errors or violations.
  • Special Warning [2]: A potential discrepancy in the data which triggers a violation but does not prohibit the job from promotion. Special Warning errors should be examined carefully and corrected as needed.
  • Fatal [3]: A critical error in the data which prohibits the entire job from promotion. Fatal errors must be corrected for the job to advance.
  • Warning [4]: A possible misalignment in the data which triggers a violation but does not prohibit the job from promotion. Warning errors should be reviewed for data accuracy.

View Rule Details

View Rule Details

To view additional details for a rule, click the Details icon [1]. The rule details tray displays information about the rule, including:

  • Rule ID [2]: A string of text and/or numbers that label a specific rule.
  • Error Level [3]: The warning which should be triggered when the data triggers errors.
  • Domain/Entity [4]: The mutually exclusive group and sub-group to which the rule applies.
  • Rule Applies To [5]: The agency and/or schools to which the rule applies.
  • Rule [6]: The prescriptive parameters that form the context of the data.
  • Business Meaning [7]: The related business parameters that form the context of the data.
  • Steps to Resolve [8]: Suggested actions to fix rule violations.
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