Scenario: Data & Business Analyst

Cleaning huge exports, joining tables, building dashboards, ad-hoc analyses, and shipping the results.

Scenarios 7 lessons ~80 min

Meet Marcus, a business analyst at a mid-sized retailer. His job is roughly 'turn data into decisions'. Here's how Python earns its keep on his typical week.

Lessons in this module

1. User story: cleaning a 4-million-row export · 10 min
   When the CSV is too big for Excel itself.
2. User story: joining six tables to answer one question · 10 min
   Stars, snowflakes, and the merge dance.
3. User story: customer cohort retention · 11 min
   Group customers by signup month, track their retention over time.
4. User story: did the change work? A quick A/B test · 10 min
   Two groups, one metric, was the difference real or noise?
5. User story: trend, seasonality, and 'is this Tuesday weird?' · 9 min
   Decompose a time series. Spot anomalies.
6. User story: a refreshing dashboard sheet · 10 min
   Build an Excel dashboard that auto-updates when the source data changes.
7. User story: shipping the analysis — narrative report · 10 min
   Turn an analysis notebook into a one-page narrative the boss will actually read.