Reviewing and promoting Foundation data

The steps associated with reviewing and validating the Foundation data are handled by using the Data Visualizer console.

The following table provides more information about each step.

Reviewing and promoting data

Use the Data Visualizer feature of the Onboarding wizard to review and, if necessary, edit your data, and later to correct any data exceptions.  

When you finish loading your Foundation data, click Finalize Review and Activate to review and validate your Foundation data. From Data Visualizer, you can review the data that you entered to ensure it is correct before you promote it. If you discover a problem in a record, you can edit the record directly in Data Visualizer. You can also make bulk edits in the Data Visualizer by using the Modify All option.

For example, if you notice that one of the Assigned Group names has a spelling mistake and the mistake is repeated in all of the Assignment records, you can use the Modify All feature to update all of the affected records in a single operation. The Modify All option allows 100 entries to be updated at a time.

Data Visualizer displays the data types in columns, grouped under the headings as shown in the following table:

If there is a large volume of data, you can limit the number of records displayed in the columns by using the filters at the top of each column.

The filters cascade downward in the data hierarchy. For example, if you filter by company, the rest of the records shown in Data Visualizer belong only to that company. If multiple filters appear at the top of a column, you can filter on multiple conditions.

The People Template Permission Groups table is not affected by the Company filter. By default, this Permission Groups table shows all of the available People Template permission groups. You can, however, apply filters within the People Template Permission Groups table that let you control which permission groups appear in the table.

To review and promote data

1. Click Finalize Review and Activate. 
2. Select from the following options to review and activate the data:  
   • Manually confirm all data is valid before creating it as production data
   • Automatically create as production data for any valid data
3. In Data Visualizer, the Organizational Structures column is open by default.
   To expand other columns, click the arrow on the column panel. 
4. Review the data to ensure that it is correct.
5. If you find a problem with a record, double-click the record to open the data-editing window. 
6. Correct the problem, then click Save to close the window. 
7. Perform one of the following actions, which displays the Activation UI:
   
   
   1. If you selected Manually confirm all data is valid before creating it as production data option in step 2, click Validate.
      The Onboarding wizard runs the validation tests, but does not promote any data until you tell it to. 
   2. If you selected Automatically create as production data for any valid data option in step 2, click Promote.
      The Onboarding wizard runs the validation tests and automatically promotes valid data to the production database.
8. If the Activation UI displays that there are no data exceptions, perform one of the following actions:
   1. If you have selected Manually confirm all data is valid before creating it as production data option in step 2, click Promote to promote the data to the production forms, and finish the job. 
   2. If you have selected Automatically create as production data for any valid data option in step 2, the job is complete.
9. If the Activation UI displays any exceptions, you must perform exception handling. To address exceptions, see the information provided in Exception-handling.
   If you receive a message related to the number of available licenses during the promotion or validation steps, see License-validation-during-a-data-load-job. 

To correct data exceptions

Use these steps to correct any data exceptions that might occur during the Activate step.

1. On the Activation UI, click Exceptions to open a list of records in the Data Visualizer that have data exceptions. This list also provides information about why the record caused the data exception.
2. Open the data editing window by performing one of the following actions:
   • To edit a single record, double-click the record. 
   • To edit multiple records, select the records that you want to update, then double-click the selection (for People and Assignment records only).
   • To edit all records in single data structure (for example, all Company records), click Modify All (for People and Assignment records only).

3. Use the Data Editing window, correct the data exception, then click Save. The Onboarding wizard removes the corrected records from the Data Visualizer. 

   If you later want to see the records that you updated, click Corrected. The wizard redisplays the corrected records that previously were removed from view.

4. Depending on how you chose to review and promote the data, click one of the following buttons:  
   • Validate—Manual, validates the corrected data and then waits for you to promote it.
   • Promote—Automatic, validates the corrected data and automatically promotes data that passes validation.
5. If the validation test finds more data exceptions, repeat Exception handling iteratively, until one of the following events happens:
   • The validation checks no longer find data exceptions
   • You choose to ignore the data exceptions and start a new onboarding session
   • You choose to delete the records that are causing the data exceptions and address those issues at a later time

Diagnosing data exceptions

Data exceptions have associated codes and messages that can help you to diagnose the cause of an exception.

To view the code and message for a specific record, select the record in the Data Visualizer. The Onboarding Wizard displays the associated code and message in the Exception Messages panel on the right side of the Data Visualizer. The code and the message appear under separate headings: Exception Codes and Exception Message. If a data exception occurs during the Promotion step, you will also see a heading for Exception Text, which contains information related to the data-promotion text.

The information under the Exception Message heading concatenates the codes and the messages. 

If multiple reasons for the exception exist, the Data Visualizer reports all of the related codes in a semicolon-separated list under the Exception Codes heading. The associated message text also appears in a semicolon-separated list under the Exception Message heading. The exception messages always appear in the same order as the codes. 

To use the Exception console

The Exception console is another tool that you can use to view and correct data exceptions. The Exception console organizes the exceptions in a tree format grouped by exception type. After you correct the exception, the Exception console stops displaying the record.

1. Select an exception type from the navigation tree. 
   Selecting an exception type lists all of the records with that type of data exception in the table.  
2. From the table, select one or more rows. By selecting multiple rows, you can perform bulk updates.
3. Use the editing panel below the table, perform one of the following actions:

   1. Update the field that contains the data exception with the correct content, then click Update Staging. If you selected more than one row in the preceding step, the change that you make is applied to all of the selected records.

      There is a pair of  icons to the right of each field:

      • Using the left icon of the pair, you can expand the text editing field to make it easier to edit very large text entries.
      • Using the right icon of the pair deletes the field contents and inserts the string NULL. Insert NULL w hen you specifically want to empty the contents of any given field. Placing NULL in the field ensures that the system interprets the field as empty.
   2. Delete the selected records by clicking Delete Staging.

Controlling which records appear in the Data Visualizer

These buttons are available in Data Visualizer to help you control the records that it displays. The buttons that you see at any given time depend on what you are doing and where you are in the Review and Activate steps.

Deleting records

To delete records from the Data Visualizer that contain data exceptions, use the delete icons at the bottom of each column.

• Delete Selected—Deletes the record or records that you select in the column.
• Delete All—Deletes all of the records in the column.