Issues Dataset Exploration Report

Streamline your issue management for peak efficiency. Dive into the complexities of issue data with Keypup's Issues Dataset Exploration Report. This essential tool delves into how issue data from project management and Git sources is meticulously imported, mapped, and integrated. By understanding the intricate taxonomy and structure of your issues dataset, you can gain clear insights into your project management challenges and workflows, paving the way for more effective problem-solving, smoother team collaboration, and optimized project outcomes.

Explore Your Issues Dataset Now!

Master Your Project’s Issues

with the

Issues Dataset Exploration Report

Streamline your issue management for peak efficiency. Dive into the complexities of issue data with Keypup's Issues Dataset Exploration Report. This essential tool delves into how issue data from project management and Git sources is meticulously imported, mapped, and integrated. By understanding the intricate taxonomy and structure of your issues dataset, you can gain clear insights into your project management challenges and workflows, paving the way for more effective problem-solving, smoother team collaboration, and optimized project outcomes.

Explore Your Issues Dataset Now!
Issues Dataset Exploration ReportIssues Dataset Exploration ReportIssues Dataset Exploration Report

From startups to large enterprises, Keypup serves all the unique complexities related to project size, structure and teams, including:

“Keypup is a highly useful and practical platform, boasting user-friendly features and lightning-fast report generation.

The service provided by customer support was excellent, showcasing their dedication to customer satisfaction. We are delighted to be part of the Keypup community.”

“Keypup has been instrumental in helping us gain a better perspective on our engineering activities and identifying bottlenecks. Its ease of use combined with its comprehensive features made a difference for us”

“Great product with great support!
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Keypup is extremely flexible in its reporting. Once you get your raw data connected, there is almost nothing it can't do. There is a wealth of tables, charts and other reports available. As Director of a software development team, I use Keypup to report on our work efficiencies to senior managment. Keypup makes this task very simple to produce each week.”

Brad B.

Director, Software Development

Deep Dive Into Your Issues Data

To build the Issues Dataset Exploration Report, we apply two filters on the report from the Issues and PRs Dataset: one date filter and one filter on the “Type” field to isolate issues only.

We then add 17 columns with populated or calculated fields to facilitate your issue data exploration. These columns include:

  • Created at: The date/time at which the issue was created.
  • Title: The title, summary, or name of the issue/ticket.
  • Sub type: The type of issue, as seen in the source project management application (e.g., Story, Bug, Epic, Task, etc.).
  • Author: The username of the person who created the issue. Note that usernames are app specific.
  • Assignees: The list of people usernames declared as being assigned to the issue. Note that usernames are app specific.
  • Body: The body of the issue in source format.
  • Labels: The list of labels tagged to the issue. Labels are app-specific and case-sensitive.
  • URL: The issue URL in the source application.
  • Due on: The due date of the issue. This due date takes into account resolved issues (e.g., a pull request resolving multiple issues will have a due on value equals to the earliest due date).
  • Project: The name of the project associated with the issue.
  • Workflow status: The team-defined status of the issue, as seen in the source project management application (e.g., In-Development, Closed, Open, etc.).
  • State: The open/close state of the issue.
  • Closed at: The date/time at which the issue was closed.
  • Story points: The number of story points (implementation complexity) that was estimated for the issue.
  • Time estimate (hours): This calculated field provides the estimated effort (in hours) to implement the issue as entered in the source application. 
  • Time spent (hours): The time spent (in hours) on the issue as entered in the source application.
  • Updated at: The date/time at which the issue was last updated.

Key Benefits of the Issues Dataset Exploration Report

Streamlined Issue Management

Discover how issue data is organized and used within your projects. This report uncovers the intricacies of issue handling, providing insights into effective management and optimization of your issue-related processes.

Enhanced Understanding of Project Challenges

Through detailed analysis of imported issue data, identify common project challenges and trends. This understanding enables you to anticipate potential roadblocks and streamline your project management strategies.

Effective Workflow Integration

Leverage the insights from this report to integrate issue data more effectively into your development workflow. By understanding the structure and mapping of issues, you can create more efficient processes and enhance team collaboration.

Data-Driven Decision Making

Utilize the detailed insights provided by the report to build and track powerful metrics and make informed decisions about project management, team assignments, and prioritization of tasks. The depth of data analysis helps you tailor your strategies to meet your project’s unique needs.

Harness the Insights from the Issues Dataset Exploration Report

The Issues Dataset Exploration Report is your key to unlocking a deeper understanding of how issues data impacts your project management. With this report, you can refine your management strategies, anticipate challenges, and enhance overall project reporting and efficiency.

Ready to transform your approach to project management? Explore the Issues Dataset Exploration Report and start optimizing your project workflows today.

Explore Your Issues Dataset Now!