End-to-end e-commerce analytics pipeline using the Olist Brazilian dataset. Raw transactional data is cleaned, merged, and transformed into order- and customer-level tables. RFM metrics are computed and clustered with KMeans. The project applies feature engineering, analytics, and visualization in Python to generate actionable business insights.
🔌 Data → 📈 Visuals → 🧮 Calculations → 🎛️ Interactivity → 📖 Insights → 🔁 Practice. 📊 Tableau Skill Development — Visual Icon Representation 🔌 Data Connection → Connecting, structuring, and preparing data sources in Tableau 📈 Data Visualization → Creating meaningful charts, KPIs
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