Data Analysis & Business Analysis Projects
Each project demonstrates the end-to-end data lifecycle, from initial collection and cleaning to final visualization and business recommendation.
E-commerce Sales Performance Analysis (Amazon Sales)
**Action:** Developed an interactive dashboard to visualize sales trends, identify top-performing products, and analyze customer behavior. Leveraged **SQL** for precise data preparation and **Tableau** for visualization.
- **Tools:** SQL (SQLite), Excel, Tableau Public
- **Impact:** Identified monthly sales trends and **three key regions for promotional focus**, demonstrating a commitment to the **100% compliance and precision** needed for critical analysis[cite: 16].
Interactive Dashboard:
(If the interactive dashboard doesn't load or for a full-screen view, you can access it directly on Tableau Public: Amazon Sales Analysis Dashboard)
Customer Churn Prediction Model (Conceptual)
**Action:** Developed a preliminary machine learning model in Python to analyze customer behavioral data and predict potential churn risk. This effort mirrored the **logical and systematic approach** I used when interpreting technical schematics in operational logistics[cite: 4].
- **Tools:** **Python** (Pandas, Scikit-learn), SQL, Jupyter Notebook
- **Outcome:** Identified key factors contributing to customer churn (e.g., specific service usage), allowing for the suggestion of targeted retention strategies.
Market Basket Analysis for Retail Cross-Selling
**Action:** Explored large transactional datasets to discover strong association rules between purchased items using the **Apriori Algorithm** concept. The analysis ensures **detailed logistical coordination** in product placement, reflecting my past experience in supply chain management[cite: 29].
- **Tools:** Python (Conceptual modeling)
- **Outcome:** Provided insights into popular product combinations with a high "confidence" score for improved product bundling and targeted cross-selling offers.