Import data from Jira Cloud to Google Sheets

Export issues from Jira Cloud to Google Sheets and filter them using custom JQL (Jira Query Language) to perform combined analysis and reporting.

The 4 steps to complete the setup

  1. Fill out the Title field
  2. Set up your data source
  3. Set up your data destination
  4. Configure importer's settings

1. Fill out the "Title" field

Name your importer. We recommend you pick a name that will enable easy in-app navigation for you and your team.

2. Set up your data source

2.1. Add a Connected Account

  • Click Connect.
  • Pick the Jira Account you want to connect to.
  • Sign in to the chosen Jira Account.
  • Coupler.io will need access to view your Jira data. Click Allow to grant access.

2.2. Fill out the "JQL" field

Enter a JQL query or an ID of the filter saved in Jira. The default behavior: include all issues.

To get a JQL query for the required issues, you need to set up your search filters and then click on the Switch to JQL button. Here is an example:

project = JTGS AND issuetype = Task AND status = "In Progress" AND assignee in (EMPTY) order by created DESC<br>
	

Click Show advanced to set up optional parameters for your data source.

2.3. Select the Import format

Pick the data importing format for this importer: Jira CSV export or Detailed data. Jira CSV export - the default format JIRA uses for its own CSV export.

Custom fields import is handled in the following way:
  • While importing multiple custom fields, the name of the field is specified in parentheses:
  • If one custom field contains multiple values, these values will be distributed between multiple columns in a Google Sheet. The number of columns = the number of values the custom field contains. E.g., there is a custom field "Assignees" and it has 3 values. In this case, the import output will look as follows:

Overall, we try to preserve Jira manual export rules for Jira CSV export format.

Detailed data - the format to import all data as is, including IDs, URLs and other metadata to be placed in separate columns.

2.4. Fill out the "Fields" field

Specify the names of the columns to pull from Jira, as well as their order by entering each column's name from a new line. The default behavior: select all navigable columns.

Where to get the column names?

Make the initial import with Fields empty. You’ll get your data with the names of all columns. After that you’ll be able to specify which columns you need for recurrent data imports.

3. Set up your data destination

3.1. Connect a Google Account you want to import data to.

  • Pick an account you want to connect to.
  • Sign in to the chosen account.
  • Review the contents of access rights which you are granting to Coupler.io and press Allow.
  • Confirm your choices.
  • Read the "Close this window" message and close the pop-up.

3.2. Fill out the "Sheet name" field

Name the sheet, which will be receiving data. If the sheet with this name does not exist, Coupler.io will generate a new one for you.

Click Show advanced to set up optional parameters for your data destination.

3.3. Fill out the "Cell address" field

Type in the address of the first cell where the data range will be imported. The default value is A1.

4. Configure importer's settings

4.1. Enable the Automatic data refresh

  • Select Interval
  • Select Days of week
  • Specify Time range

Check out more about Automatic data refresh.

Click Show advanced to set up optional settings for your importer.

4.2. Pick the Import Mode

Follow this link to read more about choosing a data import mode.

4.3. Add the "Last Update" column

If you want to add a column specifying the date of the last data refresh, toggle the Last Update parameter on.

4.4. Save the changes

Click Save to save the parameters or Save & Import to save the parameters and run the initial import right away.

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For any questions, feel free to email our team at  contact@coupler.io