How To Export Jira Backlog to CSV
Get deep insights into your CSV data with Sourcetable AI. Create custom charts, formulas, and reports. No Excel skills required.
Introduction
Exporting your Jira backlog to CSV allows you to manage and analyze your project data efficiently.
This guide will take you through the step-by-step process of exporting your backlog data from Jira to a CSV file.
We'll also explore how Sourcetable lets you analyze your exported data with AI in a simple to use spreadsheet.
Exporting Jira Backlog Data to CSV
- There is no built-in solution for exporting issues directly from the Jira backlog dashboard. However, you can still achieve this by following a series of steps that involve JQL queries, Python scripting, and CSV combiner tools.
- You can export filtered issues from the project "Issues" section using JQL. This involves creating a specific JQL query to retrieve the issues you need. An example JQL query is: <code>project = "YourProject" AND issue in (issue1, issue2, issue3, ...) ORDER BY created DESC</code>.
- To filter issues accurately, you may need to extract issue names from the HTML source code of the backlog dashboard. This process can be automated using a Python script that parses the HTML and collects the necessary issue identifiers.
- Once you have filtered the issues using your JQL query, navigate to the Advanced Search screen from the Filters menu. Use the Excel or Export buttons here to export the data to CSV. Ensure you are a registered user to utilize these features.
- The Atlassian issue export function has a size limit. If you encounter this limit, consider exporting the issues in batches and then using a CSV combiner tool to merge the files together.
- By combining the use of JQL queries, Python scripting, and CSV combiner tools, you can effectively export your Jira backlog data to a CSV file, despite the absence of a direct export feature in Jira.
Introduction
Using JQL to Filter Issues
Extracting Issue Names
Exporting Issues
Handling Export Limitations
Conclusion
How to Export Your Jira Backlog to CSV
Exporting issues from your Jira backlog to CSV format can streamline data analysis and sharing. Below is a step-by-step guide to exporting your Jira backlog effectively.
Using JQL to Filter Backlog Issues
Jira does not offer a built-in solution to export issues directly from the backlog dashboard. To work around this, use JQL (Jira Query Language) to filter and export backlog issues. Access the project "Issues" section and apply appropriate filters to capture the backlog issues you need.
Exporting Issues to CSV
After filtering the backlog issues using JQL, navigate to the top right corner of the Issue Navigator page. Use the Export button to export your filtered issues. Select "CSV" from the export options. This functionality is available for both Jira Cloud and Jira Server/Data Center environments.
Handling Large Exports
If the number of issues exceeds the Atlassian export function size limit, consider exporting in batches. You can use a CSV combiner tool to merge multiple CSV files into a single document.
Advanced Extraction Methods
For advanced users, using a Python script to extract issue names directly from the HTML source code of the backlog dashboard is an alternative method. This can be particularly useful for complex filtering requirements.
Try Sourcetable For Free
Do anything you want in a spreadsheet using AI. No Excel skills required
Use Cases Unlocked by Jira Backlog
Managing Software and Service Projects |
Jira can be utilized to manage both software and service projects effectively. By creating a structured backlog, teams can track, prioritize, and resolve issues seamlessly. |
Tracking and Managing Issues |
Jira backlog allows teams to track issues efficiently. With functionalities like ranking issues and using quick filters, teams can address high-priority tasks promptly, ensuring smooth project execution. |
Planning Across Teams and Projects |
Jira backlog is instrumental in planning work across multiple teams and projects. It helps synchronize tasks, releases, and overall project management, enhancing collaboration and productivity. |
Optimizing Workflow and Prioritization |
Automation and third-party apps for changing ranks, along with drag-and-drop ranking, simplify backlog management. This enhances prioritization, making workflows more streamlined and efficient. |
Enhancing Visualization and Collaboration |
Using Jira backlog improves visibility into task dependencies and roadblocks. This visualization aids teams in collaborating more effectively, optimizing workflows, and ensuring tasks are completed on time. |
Refining Backlog with Best Practices |
Implementing templates and Scrum refinement are best practices for effective Jira backlog grooming. These techniques ensure that the backlog remains organized, relevant, and actionable. |
Planning and Executing Sprints |
Jira backlog is essential for planning and executing sprints. Teams can build and manage a backlog of issues, set up sprints, and monitor progress, facilitating a clear path to project completion. |
Data-Driven Decision Making |
Jira helps teams make data-driven decisions by providing insights into task completion rates and workflow optimization. This analytical approach leads to improved project management efficiency. |
Sourcetable: A Powerful Alternative to Jira Backlog
Sourcetable offers a streamlined solution for managing your data across multiple sources with a familiar spreadsheet interface. Unlike Jira backlog, which is tailored for managing tasks and projects, Sourcetable excels in providing real-time data querying and manipulation.
With Sourcetable, you can seamlessly collect, query, and analyze data from various databases in one centralized location. This capability allows for efficient data management and instant access to crucial information, enhancing decision-making and productivity.
The spreadsheet-like interface of Sourcetable simplifies complex data operations. Users can execute real-time queries and manipulate data with ease, offering a more intuitive and agile experience compared to traditional project management tools like Jira backlog.
Sourcetable's unique approach to data management makes it an excellent alternative for businesses needing unified data operations and real-time insights. By centralizing data access and analysis, Sourcetable empowers teams to work smarter and more efficiently.
Frequently Asked Questions
Is there a built-in solution for exporting Jira backlog issues directly to CSV?
No, there is no built-in solution for exporting issues from the backlog dashboard directly.
How can I export filtered issues from Jira?
You can export filtered issues under the project 'Issues' section using JQL.
What is a method for filtering issues by name in Jira?
You can filter issues by their names using the JQL query: project = '
How can I get the list of issue names from the backlog dashboard for export?
You can extract issue names from the HTML source code of the backlog dashboard using a Python script.
What should I do if the export function has a size limit?
You can use a CSV combiner tool to merge the exported issues together.
Conclusion
Exporting your Jira backlog to CSV is crucial for in-depth data analysis. Follow the outlined steps to ensure a smooth export process.
After exporting, leverage advanced analytical tools for better insights. Sign up for Sourcetable to analyze your exported CSV data with AI in a user-friendly spreadsheet.
Try Sourcetable For Free
Do anything you want in a spreadsheet using AI. No Excel skills required.
Recommended Guides
Get insights into your CSV data
Turn your data into insights in seconds. Analyze your CSVs using natural language instead of complex formulas. Try Sourcetable for free to get started.