Aglet

Prioritize join fanout issues by decision impact

Fanout deserves urgent attention when it changes a number used to reconcile money, capacity, quality, or an operational threshold. Prioritization should distinguish a broad measure error from a narrow label or definition question, using observed report dependencies rather than guessed query volume.

Decide where the work belongs

  1. Name affected decisions

    List decisions that consume the measure and state the expected grain for each. Record whether the total is compared with another system, used to approve work, or read only as directional context. A misleading aggregate should carry more weight than a cosmetic row repetition.

  2. Map the multiplication path

    Identify cards, tables, exports, and saved reports sharing the join or metric definition. Mark the first relationship that multiplies the intended grain and separate surfaces that intentionally show child detail from those presenting a parent total.

  3. Set an actionable queue

    Queue metric repair when the documented grain is violated, definition review when stakeholders disagree about the unit, or label repair when the aggregation is valid but unclear. Assign an owner who can approve the measure semantics and fixture.

What to carry forward

Prioritize the issue when a documented parent measure is inflated or understated by an unhandled one-to-many relationship. Put definition review ahead of implementation when the business unit is unclear; otherwise queue a reproducible metric repair with representative join data.

Technical background: PostgreSQL documentation.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

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