Overview
CSV or comma-separated values file is a popular way to store data in textual files. Many systems, such as spreadsheets and SaaS applications offer a way to export data in a CSV format.
Quantive can import any CSV file and use it as a data source for generating insights and metrics.
Example
The following is an example of a CSV file:
Name,Position,Salary
John Peters,CEO,100000
Mark Jacobs,CFO,95000
Tony Shaw,VP Sales,70000
In this example, the first row - Name,Position,Salary, is the header row that gives the names to the columns.
Prerequisites
The CSV file that you import must have headers.
Procedure
Perform the following:
In Quantive, navigate to Settings > Data Sources screen
Click the Select data source button
From the Choose a connector dialog, select the Files tab and then CSV file
Enter a name for this data source.
In the URL field, enter the publicly accessible URL of the CSV file.
For example, this could be a file shared on pCloud or Github Gists.
Please note that files from Dropbox aren't supported for this connector and files from Google Drive would need to be converted to .csv first.Click Connect data source.
Define who will have access and who will be able to administrate this connection using Data Connection permissions.
Choose your file and click on the Add data source button.
Give a name of your data source, something that makes sense to you and select the sync schedule (how often you want this data source to be synced automatically)
Click on the Add my data source button .
Define who will have access and use the information in this entity to create insights and automate KRs and KPIs using the Data Source permissions.
Click on the Finish button.