To ensure data ingestion pipelines function correctly over time, your data must maintain a consistent structure from upload to upload. We define these structure requirements in data contracts for each data source.
You will now receive immediate feedback if your uploaded data does not match the data contract. This article explains how to resolve data contract errors.
Most errors can be resolved during file upload, similar to Data Importer data sources. However, some data sources and errors can only be validated after the data has been uploaded.
Resolve data errors during the upload ("Dynamic Data Contract Check")
Once your data is uploaded and column mapping is confirmed, you will be taken to the "Review & Finalize" screen. Errors will be highlighted in red.
Use the panel on the right to review all errors. Clicking on any issue will filter the rows with errors, and a message will explain what needs to be fixed.
Below are the different actions you can use to resolve the errors:
Use automatic fix suggestions
The Data Importer can automatically resolve certain errors, such as incorrect date formats.
To apply the automatic fixes, click Fix All, and the system will correct these issues for you.
Replace all rows with errors
Some columns must be filled in to upload the data. For mandatory columns with drop-down lists (picklists), you can replace all rows with errors to meet the required standards:
Replace a Specific Cell Value: Manually correct individual cells with errors.
Replace All Similar Values: Automatically replace all occurrences of a value (e.g., replacing "kilowatt hour" with "kWh" across all rows).
Review All Replacements: Review unique values and map them to standard values—useful when multiple variations exist.
For mandatory columns that are not a picklist, you can click on "Use a different action"
Delete the invalid rows: Removes all rows with errors.
Fill empty values: Assigns a single default value to all empty rows in the column — useful when most rows should have the same value.
Find and Replace Specific Values
Replace specific values in any column.
Delete Rows
Remove rows containing errors.
Select specific rows to be deleted.
Filter Errors and Export and Fix Errors Offline
Filter View: Choose to display only rows with errors or only valid rows to streamline your review.
Export Errors: Download all rows with errors into an Excel file, correct them offline, and re-upload the file.
Click the information icon next to each column name to view detailed descriptions.
To adjust column mapping, click "Previous" or "Remap this Column" in column actions.
Types of data contract errors
Below are common data contract errors and their recommended resolutions:
Errors | Suggested ways to resolve |
Facility / Business Unit name is invalid – does not match the list in the app |
|
Value is invalid – does not match a standard AQ list (e.g., countries, currencies, weight units) or a custom list | Use “Replace All Similar Values” to map the alternative name of the value to one from a drop-down list |
Cell must be filled | Fill values one-by-one or use “Fill empty values” to fill all |
Formatting error (e.g., incorrect date format) | Most of the date formatting will be picked up by the automatic fix suggestions. Otherwise, use “Find and Replace” to correct the values. |
Resolve data errors after the upload ("Static Data Contract Check")
For some data sources and errors, validation can only occur after upload. If this happens, a new task with appear in the Task tab and file status will change to "Processing". You will also receive a notification to review data errors.
Steps to Resolve Post-Upload Errors:
Go to the Tasks tab for the affected data source.
Click "Check Data Errors" to view the list of contract errors.
Correct the errors and re-upload the entire file.
⚠️ Note: You must re-upload the entire file, not just the rows with errors.
Examples of Post-Upload Errors & Fixes
Error | How to Fix It |
Unexpected file format | Save the file in the same format as the original upload (e.g., .xlsx or .csv). |
Missing column | Check if the column was removed, renamed (including case changes), or the table header position was changed |
Unexpected value | Ensure that all values match an approved list for this column or request a data contract change to add a new value. |
Unexpected value type | Ensure all values match the required data type for this column (e.g., date, number, text). |
Unexpected empty value | Ensure all mandatory fields are filled. |
Duplicate values | Remove any duplicate entries. |
Requesting a change in data contract
In rare cases, your data structure may change significantly, requiring a data contract update (e.g., adding a new value to a custom drop-down list).
To request a change:
Contact Support and explain the required modifications.
Our Customer Success team may reach out to discuss the scope of changes.