Business Analytics
Lab Curriculum.

BUG FOUND: analysts who can make a chart, but cannot answer a business question reliably.

$ step-01 brushup // weeks 1–2 — Topics taught:

1. Business questions first: defining a KPI before building a chart.
2. Excel / SQL basics for business data: cleaning, joining, aggregating.
3. Dashboard basics: measures, filters, and choosing the right chart.
4. Segmentation and cohort basics.
5. Variance analysis: actual vs target / prior period.
6. Writing an insight: claim, evidence, action — not just a chart title.

$ step-02 debug // weeks 3–4 — Production Debugging. Tools: Excel, SQL, a dashboard tool, sample business data.

• BUG #1: Two teams report different revenue for the same month — find the definition / filter difference, align it, document the single definition.
• BUG #2: A KPI jumps with no business change — trace it to a data / date / inclusion error, fix it.
• BUG #3: A dashboard misleads because of a wrong aggregation (e.g. averaging averages) — correct it, show the right number.
• BUG #4: A segment analysis is biased by a missing group — find the missing group, correct the analysis, state the limit.

$ step-03 navigate // weeks 5–7 — Codebase / System Navigation:

• Trace a KPI to its source data and definition across multiple reports; build a KPI dictionary.
• Fix an upstream definition error and prove downstream reports change correctly.
• Compare a new analysis with a prior one: what changed, what is comparable, what is not?
• Present findings to a mentor as a decision-maker: recommendation, evidence, risk.

$ step-04 ship // weeks 8–9 — Shipping Features: capstone — a decision dashboard + written recommendations for a real business problem, with data sources and caveats.

$ ship → PROOF — exact output: dashboard, KPI dictionary entry, and a recommendation note with evidence and caveats.

$ run --lab business-analytics → ✓ SHIPPED, job-ready