Summary
The CSV User Import Integration lets you bring users into KnowledgeCity from a CSV file and keep them in sync using configurable field mapping. You upload a file, match each column to the corresponding KnowledgeCity user field, and choose how new and existing accounts are handled. This removes the need to create or update learner records one at a time.
Introduction
The CSV User Import Integration is part of the KnowledgeCity Integrations product. It reads user records from a CSV file and creates or updates the matching accounts in KnowledgeCity, with a mapping step that connects the columns in your file to the user fields in the system.
This integration is typically used by administrators who onboard learners in bulk or who keep KnowledgeCity aligned with a roster maintained in another system. It solves the problem of manual, one-by-one account management by turning a prepared file into a repeatable import and sync operation.
Key Concepts
- CSV file: the source file containing one row per user, with columns for the user attributes you want to import.
- Field mapping: the configurable step where you connect each column in your file to the corresponding KnowledgeCity user field, so the data lands in the right place.
- Import new users: the action of creating accounts for rows in the file that do not yet exist in KnowledgeCity.
- Update existing users: the action of modifying accounts that already exist, so their records stay current with the file.
- Match-by field: the identifier (such as email, employee ID, or username) used to decide whether a row corresponds to an existing account or a new one.
- Import options: the settings that control how the import behaves, including how to handle missing values and which notifications to send.
- Synchronization: the ongoing use of imports to keep KnowledgeCity user records aligned with the source roster over time.
Steps to Follow
Prepare Your CSV File
You begin by assembling a CSV file with one row per user and a header row that names each column. Include the attributes you want to bring into KnowledgeCity, such as name, email, and any organizational identifier you use to distinguish accounts. Make sure the values that identify each user are accurate and consistent, because they determine whether a row is treated as a new account or a match to an existing one.
Upload the File
You start the import by uploading your .csv file into the integration. Once the file is accepted, the system reads its columns and prepares the mapping step so you can tell KnowledgeCity what each column represents.
Map the Columns to User Fields
You then match each column from your file to the corresponding KnowledgeCity user field. This field mapping step is where the configuration happens: columns you map are imported into their matching fields, and any column you leave unmapped is not imported. Review every relevant column to confirm it points to the correct field before continuing.
Choose How Accounts Are Handled
You decide whether the import should create new users, update existing users, or both. You also select the match-by field used to identify existing accounts, so the system can tell an update apart from a new record. Choose an identifier that is unique and reliable across your roster.
Configure Import Options
You review the remaining import options before running the job. These settings govern how the import behaves for edge cases in your data and which notifications are sent to affected users. Set them to match how you want new and updated accounts to be treated.
Run and Verify the Import
You run the import and then confirm the results. Check that new accounts were created, that existing accounts were updated as expected, and that any rows that could not be processed are reviewed and corrected. Spot-check a few records against your source file before treating the import as complete, and re-run the process whenever your roster changes to keep the two in sync.
Conclusion
The CSV User Import Integration turns a prepared CSV file into a repeatable way to create, update, and sync KnowledgeCity user accounts. By mapping your columns to the right fields and choosing how new and existing users are handled, you keep your learner records accurate without managing them one at a time.