de-problem

name	de-problem
description	Define the business problem, persona, and analytical questions for a data engineering project before choosing tools or writing code. Use when the user says 'I want to build a pipeline for...', 'where do I start', 'what should I build first', or jumps straight to tools without a clear problem statement.

Skill: Define Business Problem

Purpose

Determine who needs what, to make what decision before touching any tools. This is the cheapest step to get wrong and the most expensive to skip — a pipeline that runs beautifully but answers no useful questions is a failed pipeline.

When to stop at this skill

Only move to /sources when docs/business_problem.md has all 5 sections listed in DONE WHEN.

Steps

Step 1 — Identify Persona

Ask (or infer from the user's description): "Who will look at the output of this pipeline, and what will they do differently because of it?"

Write in this format:

"A [role] at a [type of organization] needs to make decisions about [specific problem]."

If the user doesn't know their persona, ask directly: "Who is the end consumer — yourself for a portfolio project, a manager reading reports, or another system consuming the data?"

Step 2 — Write Problem Statement (3 parts)

Part	Content
Context	What are users relying on today without this pipeline? (spreadsheet, nothing, manual process?)
Problem	What question/decision is currently hard or impossible to answer, and why? List 1–3 specific pain points.
Solution	What will this pipeline provide — sources, layers, serving output — at a level a non-technical person can understand.

Step 3 — Define 3–5 Analytical Questions

Each question must:

• Be specific enough to write SQL for today, even without data yet.
• Have a clear entity, metric, threshold, and timeframe.
• Not be vague like "understand trends" — use "top 10 [entities] with [metric] change > [X]% in [Y] days".

If the user gives vague questions, stress-test them: "If I were to write SQL for this question right now, what would the entity, metric, threshold, and timeframe be?"

Step 4 — Define Success Metric

NOT: "Pipeline runs without errors".

MUST BE: "Correctly answers questions 1–3 with data no older than [X] [hours/days]."

Example: "Dashboard shows correct top movers daily with data lag ≤ 1 business day."

Step 5 — Document Constraints

Always be explicit about:

• Budget: $0 or a specific number.
• Time available: X hours/week for Y weeks.
• Domain gaps: What knowledge needs to be learned.

Output

Create docs/business_problem.md using the template below. For a fill-in version, see skills/problem/assets/business_problem_template.md.

# Business Problem — [Project Name]

## Context
[What are users doing today before this pipeline exists?]

## Problem
1. [Specific pain point 1]
2. [Specific pain point 2]

## Solution
[1-paragraph pipeline description: sources → layers → serving output, in non-technical language]

## Persona
- **Who**: [role / organization type]
- **They need**: [specific decision or action this data enables]

## Analytical Questions
1. [Question specific enough to write SQL — entity + metric + threshold/timeframe]
2. [...]
3. [...]
4. [...]  ← optional
5. [...]  ← optional

## Success Metric
[Not "pipeline runs". Must tie to answering the questions above within a specific freshness window.]

## Constraints
- Budget: [e.g. $0]
- Time: [e.g. 10h/week × 4 weeks]
- Domain gaps: [...]

DONE WHEN

File docs/business_problem.md exists and has:

• Persona written as "Who at where needs what decision".
• Problem statement with 3 parts: Context + Problem + Solution.
• 3–5 analytical questions specific enough to write SQL.
• Success metric is NOT "pipeline runs".
• Constraints specify budget + time.

Next Step

After done → run /sources to evaluate each data source and create contracts.

If a later phase reveals that no source can answer a question, revisit this skill and revise the question rather than forcing the source.

References

• Template: skills/problem/assets/business_problem_template.md
• Phase deep-dive: phases/phase-0-discover.md
• Next phase: phases/phase-1-data-contracts.md