Permissions: Sponsors with a Pinnacle 21 Enterprise license can validate their data built in elluminate against P21 using their company's enterprise license.

Pinnacle 21 Enterprise is a data quality tool for ensuring clinical data compliance with CDISC standards, including SDTM, ADaM, SEND, Define.xml, and others. The Data Quality Tool enables running Pinnacle 21 Validation jobs to assess data fitness and data quality.

Access Data Quality

Data Quality and Pinnacle 21 Enterprise are enabled during study configuration. The green dot next to Data Quality indicates that it is enabled. If Data Quality does not display for a study, it may not be enabled for that study or the required privileges may be missing. Contact the elluminate Administrator for assistance.

1. Open a study from the elluminate Studies page.

2. Access Data Quality by clicking on Data Quality from the study level Details drop-down in the Master Header.

   

Create a Validation Job

1. Open the desired study and select Data Quality from the Details drop-down in the Master Header. By default, the Data Quality module opens to the Validation Jobs window. Previously configured Validation jobs (if any) will appear as tiles in this window.

   

2. To create a new Validation Job, click the plus sign in the upper right of the Master Header. A Create Pinnacle21 Data Quality Validation window displays.

   

3. Enter the following parameters to define the standard and domains to be utilized in the validation. The top four fields are entered by default based on the study level configuration and can be updated for the validation job.
   • Project: By default, values are supplied from study configuration.
   • Study: By default, values are supplied from study configuration.
   • Group (optional): By default, values are supplied from study configuration.
   • Data Package: By default, values are supplied from study configuration.
   • Name: Enter a name for the validation job.
   • Standard: Select the Standard against which the data is to be validated.
   • Controlled Terminology: Select the Controlled Terminology.
   • Data Store: Select the Data Store that contains the data to validate. Both Staging Areas and Data Marts are listed. 
   • Available Domains: Select the domains to validate. Only the domains within the selected data store display. To select multiple domains, hold the Shift or Ctrl key and click on a domain.
   • Dictionary selections: Optionally, select the dictionary version from the drop-downs. If no dictionary is selected, the defaults from Pinnacle 21 Enterprise will be used.
   • Validation Comment: Optionally, enter a comment for the validation.
4. Click Save. The validation now appears as a tile or in the list view on the Validation Jobs window.
   That validation job is now available to run at any time.

Edit a Validation Job

To edit a Validation Job, click the pencil icon and then modify the parameters as if creating a new Validation Job (described above).

Delete a Validation Job

To delete a Validation Job, click the trashcan icon and then confirm deletion when prompted.

Run a Validation Job

To execute a Validation Job, click the run icon.

This may take several minutes depending upon the quantity of domains selected. While running, the job tile will indicate a status of 'Extracting' when extracting the data, then 'Processing' when it sends the data to Pinnacle 21 Enterprise. Lastly, the job status will display as 'Completed' even if there are issues found in the validation. If there was a problem running the validation job (error received from Pinnacle 21 or a problem with authentication) the job will return with status 'Error'. Contact the helpdesk for assistance resolving errors.

Extracting

Processing

Completed

Access Validation Results

The results of the validation are then accessible under Validations.

Click Validations in the Master Header.

Under Validations is a listing of all validations that have been run for the selected study. A new entry is created in the list every time a Validation Job is run.

The listing includes the following information for each validation:

• Job Name / Job ID: The name given to the validation job / unique ID assigned to each validation.
• Status: The status of the validation job.
• Data Store: The data store containing the data that have been validated. 
• Standard: The selected standard against which the data have been validated.
• Controlled Terminology: The selected version of controlled terminology used in the validation.
• Created By: The user who executed the validation job.
• Created Date: The date and time the validation report was created.

Available Listing Actions

1. Export to Excel by clicking the Excel document icon. The Excel file downloads to the computer.

   

2. Delete the results of an executed validation job by clicking the trashcan icon.

Best Practices

• Verify prerequisites before running. Confirm that Pinnacle 21 Enterprise validation is enabled and licensing is configured for the elluminate URL, that the study has Data Quality enabled, and that the required privileges are assigned. Contact an eCS support representative for assistance if needed,
• Scope each validation job deliberately. Select the correct Data Store (Staging vs. Data Mart) and include only domains required for validation. Smaller, focused jobs reduce run time and keep findings topical, making the discovery of any findings faster, and easier to action.
• Select specific versions for Standard, Controlled Terminology, and any dictionary options in the validation job, rather than relying on defaults that can change over time. Record the choices in the Validation Comment to document the configuration. Using fixed versions ensures that repeated runs apply the same rules and reference data, producing comparable results and a clear audit trail.
• Name jobs consistently. Consider using a naming pattern that contains study, package, standard, and scope. Consistent names make tiles, history, and exported reports easy to find, compare, and submit to any regulatory reviewers if necessary.
• Iterate and compare over time. Re-run the same job after data fixes to create a new entry in Validations and track progress by reviewing validation findings and issue counts. Maintain a validation schedule aligned to data refreshes or study milestones.