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Read More →Download data analytics projects PDF material from Uncodemy: project ideas by domain, skills each one builds and what to deliver, with beginner-friendly steps.
This page lists Uncodemy's Data Analytics project PDFs, each as its own file. Good analytics projects start from a business question, use a real or realistic dataset and end with a clear insight. Below are project ideas by domain, with the skills each one builds.
Each download below is its own file. Pick what you need — a project ideas guide, a domain-by-domain starter pack, or a step-by-step project PDF.
Project ideas across retail, banking, HR, e-commerce, healthcare and marketing — each with the skills practised and the deliverable to build.
The six-step workflow for any data analytics project — from writing the business question to publishing a README — plus a curated starter dataset list.
The four most common project mistakes reviewers flag — no question, hidden cleaning, copied work, no write-up — with what to do instead.
Each download is a separate file. Show only as many cards as there are real PDFs — each with its own title, description, page count, size and file.
A good project answers a real question with data and shows your process. It uses a dataset with enough rows to need cleaning, includes at least one chart or dashboard, and ends with findings and a recommendation. A small project explained well is worth more than a large one explained badly.
Six domains, six project ideas. Each one shows the skills the project practises and the deliverable you should walk away with.
| Domain | Project | Skills practised | Deliverable |
|---|---|---|---|
| Retail | Sales performance analysis | Excel, SQL, pivot tables, KPIs | Dashboard plus a short insight report |
| Banking | Customer segmentation | SQL, Python, grouping, charts | Segment profiles and recommendations |
| HR | Employee attrition analysis | Cleaning, statistics, Power BI | Attrition drivers and a dashboard |
| E-commerce | Funnel and repeat-purchase analysis | SQL, cohorts, Power BI | Funnel chart and retention view |
| Healthcare | Appointment no-show analysis | Python, EDA, visual storytelling | Findings by patient group |
| Marketing | Campaign performance review | Excel, SQL, conversion metrics | Channel comparison and budget advice |
Six steps that work for any data analytics project, regardless of domain or tool. Follow them in order — skipping steps usually means starting over.
Ready to build projects employers actually review? Explore Uncodemy's Data Analytics course and learn from industry trainers.
