henok-m2/bank-reviews-analysis

Customer experience analytics for Ethiopian banking apps - 10 Academy Week 2 Challenge # Bank Reviews Analytics A data analytics project analyzing customer reviews for Ethiopian banking apps from Google Play Store. ## 📊 Project Overview This project collects and analyzes user reviews to understand customer satisfaction for three Ethiopian banks: - Commercial Bank of Ethiopia (CBE) - Bank of Abyssinia (BOA) - Dashen Bank ## 🎯 What We Do 1. **Scrape Reviews** - Collect user reviews from Google Play Store 2. **Analyze Sentiment** - Determine positive/negative/neutral feelings 3. **Identify Themes** - Find common topics and issues 4. **Store in Database** - Save analyzed data in PostgreSQL 5. **Generate Insights** - Create visualizations and recommendations ## 📈 Results So Far **Data Collected: 9,806 Reviews** - CBE: 8,113 reviews - BOA: 1,184 reviews - Dashen: 502 reviews **Key Themes Found:** - Account Access & Login Issues - Transaction Problems - App Performance & Speed - User Interface Design - Customer Support ## 🛠️ Project Structure bank-reviews-analysis/ ├── notebooks/ # Jupyter notebooks for analysis ├── src/ # Python source code ├── data/ # CSV files with review data ├── scripts/ # Utility scripts └── requirements.txt # Python dependencies ## 🚀 Quick Start # 1. Clone repository git clone github.com cd bank-reviews-analysis # 2. Setup environment python -m venv bank_env source bank_env/bin/activate pip install -r requirements.txt # 3. Run analysis jupyter notebook # Task 3: Database Storage with PostgreSQL ## Persistent Data Storage for Bank Reviews Analysis ### 🎯 Objective Design and implement a relational database in PostgreSQL to store cleaned and processed review data, simulating real-world data engineering workflows. ### ✅ Requirements Completed - [x] Install and configure PostgreSQL database - [x] Design relational database schema for banks and reviews - [x] Create tables with proper constraints and relationships - [x] Insert cleaned review data from CSV files - [x] Write SQL qu …