A limited number of fields for User Accounts can be updated in Bulk using a spreadsheet upload. The spreadsheet can be downloaded from the platform, modified, and reuploaded.
- Download
- Edit the .csv
- Upload
- Match the headings
- Adding Tags and Value Conversions
- Final Confirmation
Download
As a Manager account, navigate to the Users view and select the "Bulk actions" option on the far-right side. Select all users and choose "Bulk download for import".
The next screen will show the thirteen available modifiable options, which can be removed if not needed from the download.
Then, click "Generate" to create the download file.
The file will be created and a download link will appear on the right-hand side.
Edit the .csv
The download file created from this process will create a file that uses the Semicolon (;) as the delimiter value, which may not automatically separate into columns when opened in a spreadsheet program.
To move the data into separate columns, select all data, and click the "Data" tab in Excel. Click "Text to Columns" to open the tool to separate the data.
Keep the data type as delimited, and click next.
In the delimiters list that follows, select "Semicolon" as the delimiter, and click "Finish"
The first column, the Trainee ID, should not be modified, as this column is the identifier for the user accounts in the Spark platform.
This allows changes to the Unique Identifiers to be made freely (Email Address, Mobile Phone, Username). Changing this field will break updates to accounts.
Keep the column headers as is, and update the fields in the spreadsheet (excluding the ID column) to the needed changes. There is no field for tags, as this will be something that can be added at the point of upload confirmation in Spark.
The fields that can be modified using the Bulk Update feature are:
| Field | Description |
| First name | The Given name of the Account Holder |
| Last name | The Surname of the Account Holder |
| Email address | The Email Address of the Account Holder |
| Status | "True" or "False" sets if the account is Active or Inactive on Spark |
| Visibility | "Yes" or "No" determines if the user shows in lists, reports, statistics, or metrics |
| Can be issued training | "Yes" or "No" determines if the user can have training content distributed to them |
| Can be sent communications | "Yes" or "No" determines if the user can be sent/will receive notifications |
| Mobile number | The mobile phone number of the Account Holder |
| Organisational unit | The Organisational Unit that the Account is associated with must be an exact match |
| Timezone | The time zone that the Account Holder operates in |
| Language | The Language for the Account Holder |
| Username | The Username for the Account |
| Start Date | The Start Date of the Account |
Data such as Organisation unit must be an exact match for existing Org Units in the platform, and status changes such as Status, Visibility, and Can be issued training/sent communications must be correctly spelled.
When editing has been completed, save the file as a comma delimited .csv and it will be ready to upload.
Upload
As a Manager account, navigate to the Users view, and select the dropdown option next to "+Create new user". Select "Bulk update users" from the options list.
Select the file or drag and drop it into the file field to complete the first step, and then click "Continue".
The second step is a validation check for the file and confirmation of the encoding type, which is automatic, so "Continue" can be clicked once more.
Match the headings
Next is the mapping the fields from the spreadsheet file to the fields in the Spark platform.
This will be a series of dropdowns that must be manually matched to the header titles from the spreadsheet. The PK/Trainee ID field must be matched in order to have the updates applied to the correct accounts in Spark.
Use the dropdowns for each of the other options that are needed to have updates applied. If there is a field that does not require any updates, it does not need to be matched.
Once this is complete, click "Continue" to move forward.
Adding Tags and Value Conversions
In the fourth step the value conversions can be applied, as well as reviewing/adding tags.
By default and in order to track the changes being made to the account, the platform automatically generates a tag with the date. This field can have additional tags added to it, which will apply to all users as part of this update.
Tags are applied to all users in the spreadsheet upload, to have separate tags on different users, different uploads will be required.
The rest of the page is dedicated to ensuring value conversions are set correctly.
Use the drop down fields to ensure that the mapping sets the correct status when the changes are applied.
The values may vary between settings.
Currently Spark will only accept the data in the format YYYYY-MM-DD, so update the spreadsheet to use that format. Spark will convert the date into the correct format for a custom trainee field.
Final Confirmation
The final step is a review, which will also highlight any fields that error and will not be updated.
If this is the case, the platform will highlight which account has an issue and indicates which value needs review. Click "View full details" to see which field is failing validation.
A possible error may be the Status change, which may not map if the field data is not a match. The error may display as follows:
This may appear if the data in the file for the Status field reads "Yes" or "No". The data will need to be entered as "True" or "False" in the spreadsheet file in order to process correctly.
Once everything is confirmed, click "Update X valid users" to process the update and apply the changes to the accounts.