Even after your data syncs with Clever, you may have data quality issues that could affect application performance. The impact of data quality issues on an application varies, however, review data quality issues is an important troubleshooting step when users are missing or experiencing problems in an application.
Types of data quality issues
If a record is flagged by a Data Error, the user or section will not appear in the application. Data errors must be resolved for users or sections to be successfully processed by the application.
If a record is flagged by a Data Warning, the user or section has a compatibility issue with the application that may result in a degraded app experience. We recommend contacting the application directly to determine the impact of a particular Data Warning. Data Warnings can often be ignored.
Viewing data quality issues
Data Warnings are specific to each application. You can view your Data Warnings via two methods:
- To view all data warnings: Support Tools > Data Quality
- To view app-specific data warnings: Select an application, select Data Quality
Support Tools > Data Quality (recommended)
On this screen you will see five pieces of information:
|Issue Type||Data Type||Field||Number of issues||Impacted Applications|
|The severity of the data quality issue. More info can be found here.||The record type affected.||The field that is being flagged for data quality issues||The number of records flagged for this data quality issue.||The applications that may be affected.|
To view details on an issue, click on the number of issues. Here you will see a description of the issue(s), the number of issues for that error, and the affected application. To view the specific records that are related to the issue, click the download button. A file will download with a list of affected records.
Clever groups issues by issue type, record type, and field. As such, when you select an issue from the main Data Quality screen, you may see multiple issues related issues on the detail screen. Example:
Fixing data quality issues
First, let's quickly review which errors must be fixed and which are optional:
Impact: High - Must be fixed
Impact: Low - Optional to fix. Contact the application directly to determine the impact on user experience.
To resolve most data quality issues, simply adjust the data in your student information system (SIS) as able. Once the updated data is received in your next sync, the data quality issue will be removed.
If you receive a data quality error about missing a specific field for all records:
- SFTP syncs: Add the field to your CSV exports and upload the updated CSV files to Clever. Directions for formatting your data files can be found here.
- SIS-managed Auto Sync: Reach out to your SIS and request that they add the field to your CSV exports. Once the updated data files are received, the data quality error will be resolved. Directions for formatting your data files can be found here.
- Clever-managed Auto Sync: Contact our support team with the following information:
- Record Type: i.e. Student, Teacher, Sections, etc.
- Name of the field in Clever: i.e. Username, State ID, FRL_status
- The exact name of the field in your SIS