PROJECT MANAGEMENT

BigQuery velocity warehouse and forecast snapshot

Nightly job that loads each team's completed Linear story points into BigQuery, recomputes a rolling velocity model.

CategoryProject Management
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule
  • ActionFetch completed points per teamLinearLinear
  • ActionAppend rows to velocity history tableGoogle BigQueryBigQuery
  • LogicRecompute rolling weighted velocity per team
  • OutputWrite forecast snapshot tableGoogle BigQueryBigQuery

What it does

This workflow turns raw delivery history into a queryable velocity model. Every night it pulls each team's completed points from Linear, appends them to a BigQuery history table, and recomputes a rolling weighted velocity per team. It then writes a forecast snapshot table containing predicted next-sprint capacity and a confidence band, ready for BI dashboards and other workflows to consume.

When to use it

Use it when you want one trusted source of truth for velocity across many teams rather than ad hoc per-sprint math. It is the data backbone other forecaster workflows can read from instead of recomputing history every run.

How it works

  1. 1A nightly schedule triggers the refresh.
  2. 2The flow fetches each team's completed points from the most recent cycle in Linear.
  3. 3It appends the rows to the BigQuery velocity history table.
  4. 4A query recomputes a rolling weighted average and standard deviation per team.
  5. 5The results are written to a forecast snapshot table with predicted capacity and confidence range.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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