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Why export your Jira data to Google BigQuery
Make a backup copy of your Jira issues
Create a backup of your Jira data in Google’s data warehouse. Automate the load of the issues filtered according to JQL queries at up to every 15 minutes. Accumulate your data from Jira and other sources in one place to easily access your actionable records.
Analyze and visualize Jira data stored in BigQuery
Export your Jira data to Google BigQuery to implement prescriptive, predictive, diagnostic, and other types of analytical methods. Combine data from different Jira projects or even different Jira instances in one place for comprehending analytics. Connect BigQuery to Data Studio or other data visualization tools to represent your Jira information in graphical format, such as real-time dashboards, charts, and so on. Get valuable insights from your datasets stored in BigQuery to shift your decision-making to a higher level.
Share data in the form of reports
Make BigQuery an integral source of information for your reporting. Use the extended date/time macros for more advanced filtering of issues loaded from Jira to BigQuery to build really powerful reports. Benefit from automated exports of queries to spreadsheet apps for better shareability of your Jira data.
What data you can load from Jira to BigQuery
Filter the issues by their current status, such as Accepted, Cancelled, etc., and load them to BigQuery with a click of a button or automatically on a schedule.
Export data based on the issue type you applied in your Advanced Search filter, for example, Task, Epic, Story, and so on.
Apply versatile date-centered criteria available in Jira Query Language, such as Created Date, Due Date, and others to load the filtered issues to your BigQuery dataset. Optimize your filtering by date and time using the macros available in the Jira to BigQuery integration.
Load the issues associated with a particular user or users. You can also import issues filtered by groups of users from Jira to your spreadsheet.
Benefit from multiple filter criteria available at JQL, and Coupler.io macros, to load accurate queries from Jira to Google BigQuery with just a few clicks or automatically on a custom schedule.
How to connect Jira to BigQuery
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Step 1. Select Jira as a source application and connect the Atlassian account30 seconds
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Step 2. Copy and paste a JQL query string or an ID of your Jira filter5 seconds
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Step 3. Select the export format: Detailed data or Jira CSV export5 seconds
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Step 4. Select BigQuery as a destination app and connect your BigQuery project2 minutes
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Step 5. Specify a dataset and table where you can load Jira issues to15 seconds
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Step 6. Run the integration or configure the frequency for automatic data refresh20 seconds
See what our customers say
"Coupler.io automatically imports the full dataset you need and it refreshes it completely on any schedule you want. No triggers necessary. And the best of all, the team is very supportive.
"The integrations are easy to set up and automate, my colleagues think I'm a genius, but it's really Coupler.io that is doing the heavy lifting.
Set up multiple integrations to count on every day
Looking to import data from Shopify, Clockify, QuickBooks, or any other app? Not a problem. Use Coupler.io to link a data source to BigQuery to automate workflows and leverage the power of spreadsheets across all your projects!
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