FreeMetricsFree Jira dashboard templates
Everything below sits on the views BigQuery Sync for Jira maintains in your dataset — no modelling, no field mapping. Ten minutes of sync setup, then these are copy-paste — and the Looker Studio one is genuinely one-click.
Looker Studio — one-click, no download
Because your Jira data lives in BigQuery, Looker Studio can open it natively — the closest thing to a hosted, click-and-go template. Enter the project and dataset you synced into, and we'll open Looker Studio with your issues_current view already connected:
Opens signed in as your own Google account; you'll authorize BigQuery access on first use. Then add charts on the ready-made views (issue_cycle_times, sprint_report, time_in_status) — each is a drag-and-drop source.
Power BI — Engineering dashboard
Connect (2 minutes)
Power BI Desktop → Get data → Google BigQuery → sign in → pick your project → dataset → check these views: issues_current, issue_cycle_times, time_in_status, sprint_report, throughput_weekly, cumulative_flow_daily → Load. They arrive typed and deduplicated.
Measures (paste into a new measure each)
Open Issues = CALCULATE(COUNTROWS(issues_current), issues_current[status_category] <> "Done")
Median Cycle Time (d) = MEDIANX(issue_cycle_times, issue_cycle_times[cycle_time_days])
Throughput / wk = AVERAGEX(VALUES(throughput_weekly[week]), CALCULATE(SUM(throughput_weekly[issues_done])))
Sprint Completion % = DIVIDE(SUM(sprint_report[completed_points]), SUM(sprint_report[committed_points]))
WIP Age (d) = AVERAGEX(FILTER(issues_current, issues_current[status_category] = "In Progress"), DATEDIFF(issues_current[created], TODAY(), DAY))Page layout
| Visual | Source | Fields |
|---|---|---|
| 4 KPI cards (top row) | measures | Open Issues · Median Cycle Time · Throughput/wk · Sprint Completion % |
| Line — cycle time trend | issue_cycle_times | done month × median cycle_time_days, legend: project_key |
| Stacked area — cumulative flow | cumulative_flow_daily | snapshot_date × issues, legend: status_category |
| Bar — time in status | time_in_status | status × avg hours_in_status |
| Matrix — sprint report | sprint_report | sprint × committed / completed / added / carried over |
Publish to the Service and schedule refresh — it reads BigQuery directly, Jira is never touched.
Tableau — Flow & delivery workbook
Connect (2 minutes)
Tableau Desktop → Connect → Google BigQuery → sign in → project → dataset → drag issues_current to the canvas; add issue_cycle_times, time_in_status, sprint_report as extra data sources (no joins needed — each view is self-contained).
Calculated fields
// Cycle Time (days) — on issue_cycle_times
[cycle_time_days]
// WIP Age (days) — on issues_current
IF [status_category] = "In Progress" THEN DATEDIFF('day', [created], TODAY()) END
// On-time sprint? — on sprint_report
IF [completed_points] >= [committed_points] THEN "Committed met" ELSE "Missed" ENDWorksheets
| Sheet | Rows / Columns | Marks |
|---|---|---|
| Cycle time trend | MONTH(done_at) / MEDIAN(Cycle Time) | line, color by project_key |
| Aging WIP | assignee_name / AVG(WIP Age) | bar, sorted desc |
| Time in status | status / AVG(hours_in_status) | bar |
| Sprint scoreboard | sprint / committed·completed·added | text table + On-time color |
Publish to Tableau Cloud/Server and schedule extracts as usual — it's a native BigQuery connection, so server-side refresh just works.
One-click .pbit / .twbx files
Downloadable template files are in final testing — email us and we'll send them to you first, or check back here.