Work Tracking Cubes

These cubes provide direct access to work tracking data from your connected providers (GitHub, Jira, etc.). Unlike the flow cubes which use pre-computed materialized views, these cubes query live tables for real-time data.

Issues Cube

Source Table: issues Description: Work items and issues tracked across GitHub, GitLab, Jira, and other platforms.

Key Dimensions

Dimension	Type	Description
id	string	Unique issue ID
provider	string	Source provider (github, jira, etc.)
number	number	Issue number
title	string	Issue title
state	string	Current state (open, closed)
type	string	Issue type (feature, bug, chore, incident, discovery)
authorUsername	string	Author’s username
assigneeCount	number	Number of assignees
commentCount	number	Number of comments
createdAt	time	When created
closedAt	time	When closed
firstResponseAt	time	First response timestamp

Count Measures

Measure	Description
count	Total issues
openCount	Open issues
closedCount	Closed issues
featureCount	Feature issues
bugCount	Bug issues
choreCount	Chore issues
incidentCount	Incident issues
discoveryCount	Discovery issues

Lead Time Measures

Measure	Description
avgLeadTimeDays	Average time from created to closed
medianLeadTimeDays	Median time from created to closed
avgBugLeadTimeHours	Average bug resolution time
avgDiscoveryLeadTimeDays	Average discovery cycle time
medianDiscoveryLeadTimeDays	Median discovery cycle time
p90DiscoveryLeadTimeDays	90th percentile discovery time

First Response Measures

Measure	Description
avgFirstResponseDays	Average time to first response
medianFirstResponseDays	Median time to first response
avgDiscoveryFirstResponseDays	Average first response on discoveries

Work Allocation Measures

Measure	Description
plannedCount	Features + chores + discoveries
unplannedCount	Bugs + incidents
plannedPercentage	% planned work
unplannedPercentage	% unplanned work

Discovery Metrics

Measure	Description
openDiscoveryCount	Open discoveries
closedDiscoveryCount	Closed discoveries
discoveryCloseRate	% discoveries closed
discoveryValidationRate	% validated into features
discoveryDiscardRate	% invalidated or discarded
validatedDiscoveryCount	Validated discoveries
invalidatedDiscoveryCount	Invalidated discoveries
featuresFromDiscoveries	Features created from discoveries
discoveryQualityIndex	% validated features shipped

Use Cases

• Sprint Planning: Track open issues by type
• Triage Efficiency: Measure first response times
• Work Mix Analysis: Compare planned vs unplanned work
• Discovery Process: Measure validation rates

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Pull Requests Cube

Source Table: pull_requests Description: Pull requests and merge requests tracked across GitHub, GitLab, and other platforms.

Key Dimensions

Dimension	Type	Description
id	string	Unique PR ID
provider	string	Source provider
number	number	PR number
title	string	PR title
state	string	Current state (open, closed)
merged	string	Whether merged (‘true’/‘false’)
isDraft	string	Draft PR flag
authorUsername	string	Author’s username
headBranch	string	Source branch
baseBranch	string	Target branch
additions	number	Lines added
deletions	number	Lines deleted
changedFiles	number	Files changed
commits	number	Number of commits
reviewerCount	number	Number of reviewers
commentCount	number	Number of comments
createdAt	time	When created
mergedAt	time	When merged
firstReviewAt	time	First review timestamp
firstApprovalAt	time	First approval timestamp

Count Measures

Measure	Description
count	Total PRs
openCount	Open PRs
mergedCount	Merged PRs
closedCount	Closed PRs (not merged)
draftCount	Draft PRs

Cycle Time Measures

Cycle time = PR created → PR merged

Measure	Description
avgCycleTimeDays	Average cycle time
medianCycleTimeDays	Median cycle time
p90CycleTimeDays	90th percentile
avgCycleTimeHours	Average in hours
medianCycleTimeHours	Median in hours

Review Time Measures

Review time = PR created → First review

Measure	Description
avgReviewTimeDays	Average time to first review
medianReviewTimeDays	Median time to first review
avgReviewTimeHours	Average in hours
medianReviewTimeHours	Median in hours

Approval Time Measures

Approval time = PR created → First approval

Measure	Description
avgApprovalTimeDays	Average time to approval
avgApprovalTimeHours	Average in hours
medianApprovalTimeHours	Median in hours
avgApprovalToMergeMs	Approval to merge time
medianApprovalToMergeHours	Median approval to merge

Code Change Measures

Measure	Description
totalAdditions	Total lines added
avgAdditions	Average lines added per PR
totalDeletions	Total lines deleted
avgDeletions	Average lines deleted per PR
totalChangedFiles	Total files changed
avgChangedFiles	Average files per PR
totalCommits	Total commits
avgCommits	Average commits per PR

PR Size Measures

Measure	Description
medianPrSize	Median PR size (lines)
p90PrSize	90th percentile size
smallPrCount	PRs < 400 lines
largePrCount	PRs >= 400 lines

Use Cases

• Code Review Efficiency: Track review and approval times
• PR Size Analysis: Identify oversized PRs
• Merge Rate: Compare merged vs closed PRs
• Team Velocity: Track throughput over time

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Deployments Cube

Source Table: deployments Description: Deployments tracked across GitHub Actions, GitLab CI, and other platforms.

Key Dimensions

Dimension	Type	Description
id	string	Unique deployment ID
provider	string	Source provider
ref	string	Git ref (branch/tag)
sha	string	Git commit SHA
environment	string	Target environment
task	string	Deployment task
currentStatus	string	Current status
isProduction	string	Production flag (‘true’/‘false’)
isTransient	string	Transient deployment flag
creatorUsername	string	Who triggered it
createdAt	time	When triggered
currentStatusUpdatedAt	time	Last status update

Count Measures

Measure	Description
count	Total deployments
productionCount	Production deployments
stagingCount	Staging deployments
successCount	Successful deployments
failureCount	Failed deployments
pendingCount	Pending deployments

Production Measures

Measure	Description
productionSuccessCount	Successful production deploys
productionFailureCount	Failed production deploys

Failure Rate Measures

Measure	Description
changeFailureRate	% failed deployments (all)
productionFailureRate	% failed production deployments

Use Cases

• Deployment Frequency: Track deploys over time
• Environment Comparison: Compare staging vs production
• Failure Analysis: Monitor failure rates by environment
• Release Tracking: Correlate deployments with releases

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Common Joins

All three cubes support these relationships:

Join	Description
Projects	Filter by project
Teams	Filter by team (via project-team links)
Users	Filter by author/creator

Example Queries

Issues by team:

measures: [Issues.count, Issues.openCount]
dimensions: [Teams.name]

PR cycle time by project:

measures: [PullRequests.medianCycleTimeDays]
dimensions: [Projects.name]

Production deployment success rate:

measures: [Deployments.productionCount, Deployments.productionFailureRate]
dimensions: [Deployments.environment]
filters: [{ member: "Deployments.isProduction", operator: "equals", values: ["true"] }]

Related

Core Concepts

• Issues - Issue types, states, and lifecycle
• Pull Requests - PR workflow and metrics
• Deployments - Deployment tracking

Analytics

• Discovery Flow - Pre-computed discovery metrics
• Delivery Flow - Pre-computed delivery metrics
• Deployment Flow - DORA metrics
• Analytics Overview - Understanding the analytics system