How to Upload a CSV Dataset (Dropbox or OneDrive)

Connecting Dropbox or OneDrive

In order to upload a CSV file into BrightGauge, you would first need to have Dropbox or OneDrive configured as a datasource. The following articles outline how to do so:


CSV Requirements

Before you get ready to upload a CSV file to DropBox or OneDrive, please note the following requirements/guidelines: 

-The CSV file cannot contain:

-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

-Once a dataset has been built from a CSV, Changes cannot be made to the CSV with regards to the:

-File name

-Column titles

-Column arrangement

-Number of columns

The overriding (or updated) CSV's moving forward, must be identically configured to the original CSV that was used to create the dataset, with regards to the components just mentioned above.



Accessing "Datasets" Page and "Upload CSV"

Open your Data menu on the top right-hand corner of the screen. Then select "Datasets".



Once on the "Datasets" page, at the top right of the page, click on the "Upload CSV" option. 



Configure CSV Dataset "Overview"

Select either Dropbox or OneDrive from the "Datasource" dropdown and configure the rest of the necessary fields:

Image_2019-11-21_at_1.01.13_PM.png-Select Datasource (#1 Above)

-Name your Dataset (#2 Above)

This is the name for your new dataset that will pull the data from your Dropbox csv file

-Click on "Choose File" to access the File Search (#3 Above)

Type the name of your CSV file into the search box and hit "Enter" on your keyboard. 

(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.)


It might take some time for the search to occur, but eventually, a blue link should appear below.  Click on the desired link to select your CSV file for upload.


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

Once a file is selected, you'll be redirected back to the main dataset overview page.

- Choose the sync frequency (#4 above)

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. 

-Check the "Contains Header Row" box if the CSV file has a header row. If it does not, you will be able to specify these column headers in the next section.


-Click "Choose Field types" (#5 in the screenshot above) to continue to the next step



Set CSV Dataset "Field Types"

The last step is to name the columns (if no header row) and 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



Once the field types have been set, click on the "Test Field Types" button at the bottom of the page. This will verify that all the selected field types match up with the content in the CSV columns. 


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


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