What the Capstone Asks of You

This project pulls together everything from the course: cleaning a real, imperfect dataset, exploring it to find a genuine question worth answering, building a dashboard around that question, and presenting the finding as a narrative someone could act on. It's the difference between knowing each skill in isolation and running the full workflow end to end.

Picking a Question Worth Answering

The strongest capstones start from a specific, decision-relevant question rather than "let's see what's interesting in this data." Spend real time here — a sharp, narrow question is far easier to deliver well than a broad one that never quite resolves into a clear finding.

The Deliverables You'll Produce

You'll submit a documented cleaning process, an exploratory analysis showing how you arrived at your focus, an interactive dashboard built around your core question, and a short narrative presentation of your findings and recommendation. Each deliverable maps directly to a module you've already completed.

How This Project Will Be Evaluated

Evaluation weighs the clarity of your question, the soundness of your cleaning and analysis decisions, whether your dashboard actually serves the question you set out to answer, and whether your narrative would convince someone unfamiliar with the data. Visual polish matters, but it's not the top priority.

Common Pitfalls From Past Cohorts

The most common issues aren't technical: picking a question too broad to answer well, skipping documentation of cleaning decisions, building a dashboard that shows everything instead of answering the actual question, and running out of time because scoping happened too late.

Conclusion

The capstone isn't a test of any single skill — it's a test of judgment across the whole workflow, from a messy dataset to a decision someone can act on. Treat it the way you'd treat a real analytics request, because that's exactly what it is.