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Backlog Item Predictability

The Backlog item predictability dataset is designed to capture and analyze data related to backlog items in software development projects. This dataset aims to assess the predictability of backlog items, helping teams better understand and manage their workloads. Teams can gain insights into the predictability of their backlog items, identify areas for improvement, and make more informed decisions about resource allocation, scheduling, and prioritization.

note

In the parent portfolio item hierarchy, the topmost parent portfolio item must have been closed within the last 13 months. Any top portfolio item closed beyond the entitlement period will be excluded.

The following are the components of this dataset:

Attribute NameDescription
Closed dateDate on which the work item is closed
Closed monthMonth on which the work item is closed
Closed quarterQuarter on which the work item is closed
Completed dateDate on which the work item is completed
Completed monthMonth on which the work item is completed
Completed quarterQuarter on which the work item is completed
Lagging count of closed monthsCount of months that have elapsed since the first data record until the current month
Lagging count of closed quartersCount of quarters that have elapsed since the first data record until the current quarter
Lagging count of completed monthsCount of months that have elapsed since the first data record until the completed months
Lagging count of completed quartersCount of months that have elapsed since the first data record until the completed quarters
Last refresh dateDate of the most recent update or refresh of data in a dataset. It is in date format.
Sys_sourceUnique identifier for the source
Work item created dateDate on which the work item is created
Work item planning levelPlanning level of the work item
Metric NameDescription
Story pointsSummation of story point assigned to the work item
Backlog item countCount of backlog items in an iteration