This article describes how to upload a CSV file from Dropbox or OneDrive to BrightGauge. To upload a CSV file into BrightGauge, you must first add Dropbox or OneDrive as a datasource. Please refer to the following articles for instructions:

• Connecting to Dropbox
• Connecting to OneDrive

CSV Requirements

CSV files cannot contain the following:

• Blank rows
• Blank column headers
• Duplicate column headers
• Symbols in column headers
• Column headers can be no longer than 25 characters long
• Numbers cannot have commas

After a dataset has been built from a CSV, the following parts of the CSV cannot be changed:

• File name
• Column titles
• Column arrangement
• Number of columns

Updated CSVs must be identically configured to the original CSV that was used to create the dataset.

Upload a CSV

To upload a CSV:

1. Select DATA > Datasets.

   

2. Click Upload CSV.

   

3. Select either Dropbox or OneDrive from the Datasource menu.

   

4. Enter a name for the dataset. This is the name for your new dataset that pulls the data from your Dropbox CSV file.

5. Enter the file path of the CSV file. Type the name of your CSV file into the search box or click Choose File. If the .CSV file was recently added to the Dropbox or OneDrive account, please allow a few minutes for it to sync before trying to search and create a dataset from it. Please allow time for the search to locate the file.

   Note: If an Enterprise Dropbox account was used to connect Dropbox to BrightGauge, the file must be located under the folder of the user who authorized the connection. For personal Dropbox accounts, the file may be placed in any folder within the account. For OneDrive accounts, make sure the file is located in a folder, not directly in the main OneDrive account folder.

   

   Tip: If you are having trouble finding your files in the search, type .csv into the search field and wait a bit for your files to show.

   After a file is selected, you are redirected back to the main dataset overview page.

6. Select the Contains Header Row option if the CSV file has a header row. If it does not, you can specify these column headers in the next section.

7. Dashboard Sync Frequency: Your dataset will sync when one of its gauges is up on a dashboard. For further explanation on a dataset's Dashboard Sync Frequency, please refer to this article.

8. Click Choose Field Types to assign the field types to each column from the CSV file. To preview the data in a field, click the black 'i' icon beside the dataset field name. Four field types are available:

   • Text
   • Number
   • Date Time: All values must be in the following format: YYYY-MM-DD hh:mm:ss:nnnn and in UTC time.  BrightGauge will convert the UTC time into your local timezone.  If it's not in UTC time, then the time (and possibly date) will be off.
   • Boolean: True or False

   

9. Click Test Field Types to verify that all the selected field types match up with the content in the CSV columns. 

   

10. If all fields test successfully (✓), click Finalize Dataset. If any field returns an error (!), please review the selected field type and confirm it is set correctly.

11. 

12. If your dataset has a client column, pick which one it is to make sure your Client Mappings work correctly. Otherwise you can leave it as "No client column".