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Agility Datasets

Agility datasets provide organizations with the foundation to explore, analyze, and visualize agile development data effectively. These datasets enable teams to gain actionable insights into work item status, velocity, sprint progress, backlog health, and defect trends, fostering data-driven decision-making and alignment with organizational goals. With seamless integration into Agility the datasets ensure accurate and up-to-date reporting to optimize project outcomes and enhance development efficiency.

Agility datasets are categorized in the following category:

  • Prebuilt dashboard datasets are meticulously crafted using comprehensive data directly sourced from Agility. Tailored to specific scenarios, use cases, and dashboards, these datasets ensure seamless integration, delivering immediate insights for tracking key metrics and fostering efficient development and portfolio management.

  • Self-service datasets empower users to independently create custom dashboards and generate ad hoc reports. Designed for intuitive use, they offer the flexibility to explore and analyze data based on specific needs, enabling faster decision-making and enhancing business agility.

The following table lists the agility datasets:

DatasetsDescriptionCategory
Agility calendarProvides scheduling data for project activities, iterations, and milestones.Self-service
Agile earned by valueTracks Agile earned value across planning levels and work items.Prebuilt
Backlog group hierarchyDisplays backlog hierarchy across planning levels.Self-service
Backlog item predictabilityMeasures the accuracy of backlog item completion estimates.Prebuilt
Backlog item responsivenessTracks the time taken to process backlog items.Prebuilt
Backlog item throughputShows the number of backlog items completed over time.Prebuilt
Blocked backlog item throughputDisplays throughput for backlog items that were blocked.Prebuilt
Defect snapshot dailyProvides daily defect trend data.Self-service
Defect snapshot monthlyProvides monthly defect trend data.Self-service
Defect snapshot weeklyProvides weekly defect trend data.Self-service
Defect summarySummarizes defect distribution and trends.Prebuilt
Defect trend by planning levelTracks defect trends across planning levels.Prebuilt
Issue baseContains details of issues, including status and ownership.Self-service
Issue linksDisplays relationships between issues.Self-service
Issue summaryProvides an overview of issue trends and distribution.Prebuilt
Iteration planned vs actualCompares planned versus actual iteration performance.Prebuilt
Planning level hierarchyDisplays the hierarchical structure of planning levels.Self-service
Planning level programDisplays program-level details within the planning hierarchy, including associated backlog items and portfolio items.Self-service
Portfolio item advancedProvides detailed portfolio item attributes.Self-service
Portfolio item baseContains fundamental portfolio item data.Self-service
Portfolio item burn upTracks portfolio item progress toward completion.Prebuilt
Portfolio item daily snapshotProvides daily snapshots of portfolio items.Self-service
Portfolio item dependencyDisplays dependencies between portfolio items.Self-service
Portfolio item hierarchyShows the hierarchical structure of portfolio items.Self-service
Portfolio item monthly snapshotProvides monthly portfolio item snapshots.Self-service
Portfolio item ownerDisplays ownership details of portfolio items.Self-service
Portfolio item strategic themesTracks portfolio items based on strategic themes.Prebuilt
Portfolio item strategic themes baseProvides baseline data on strategic themes.Self-service
Portfolio item summarySummarizes portfolio item progress and distribution.Prebuilt
Portfolio item time in statusDisplays the time portfolio items spend in each status.Prebuilt
Portfolio item weekly snapshotProvides weekly snapshots of portfolio items.Self-service
Request advancedContains detailed request-related data.Self-service
Request baseProvides fundamental request data.Self-service
Request linksDisplays relationships and dependencies between requests.Self-service
Task baseProvides fundamental task details, including status and assignments.Self-service
Task countsProvides the total number of tasks across different work items, aiding in workload analysis and progress tracking.Self-service
Task ownerDisplays ownership details for tasks.Self-service
Test baseProvides foundational data for test cases, executions, and results.Self-service
Test countsProvides the total number of test cases, helping track testing efforts and coverage.Self-service
Test ownerDisplays ownership details for test cases and executions.Self-service
Test trendTracks overall test execution trends over time.Self-service
Test trend monthlyDisplays test execution patterns and outcomes on a monthly basis.Self-service
Test trend prebuiltProvides prebuilt test execution trends for quick analysis.Prebuilt
Test trend weeklyTracks weekly test execution trends and pass/fail rates.Self-service
Time spentCaptures time spent on various work items and activities.Self-service
Work item advancedProvides detailed work item attributes for in-depth analysis.Self-service
Work item baseContains fundamental work item details, including status and priority.Self-service
Work item countsProvides the total number of work items, enabling tracking of workload and progress.Self-service
Work item dependencyDisplays dependencies between work items.Self-service
Work item goalsTracks work items linked to strategic goals.Self-service
Work item in statusShows the current status of work items across categories.Prebuilt
Work item ownerDisplays ownership details for work items.Self-service
Work item snapshot dailyCaptures a daily snapshot of work item progress.Self-service
Work item snapshot monthlyProvides a monthly view of work item trends.Self-service
Work item snapshot weeklyTracks weekly changes and progress of work items.Self-service
Work item summarySummarizes work item distribution, status, and progress.Prebuilt

Accessing Work Item Data from Snapshot Datasets

The work item grain has been removed from snapshot datasets to enhance performance. You can still access work item-level data by combining data from multiple datasets. This ensures efficient data retrieval while maintaining performance optimization.

To analyze work item-level data, you need to blend datasets to derive the required insights.

Steps to retrieve work item data

  1. Use the snapshot dataset to obtain data at the date level.
  2. Join the snapshot dataset with the work item count dataset using the calendar date attribute.
  3. Further, join the work item count dataset with the work item base dataset using the work item attribute.

This method enables you to view detailed work item-level data for specific dates while leveraging the optimized performance of the snapshot datasets.