Data Analysis Projects - SQL Business Case & Aerofit Business Analysis This repository showcases two data-driven projects focused on SQL-based analysis and insights derived from real-world datasets. The projects demonstrate expertise in querying, analyzing, and presenting data to support business decisions.
Project 1: SQL Business Case Analysis Overview This project involves detailed SQL analysis of customer orders, payment behaviors, and delivery trends to provide actionable insights for business optimization.
Key Objectives Understand customer behavior and order trends. Identify operational inefficiencies and suggest optimizations. Analyze geographical sales patterns and delivery performance. Insights Derived Year-over-Year Growth: Orders increased by 15% between 2017 and 2018. Peak Order Times: Most orders were placed during the morning (6 AM - 12 PM), accounting for 35% of total orders. Delivery Analysis: States with delivery delays of up to 5 days were identified, providing opportunities to improve logistics. Freight Costs: Certain regions had 20% higher freight costs than the average, suggesting optimization strategies. Tech Stack Database: Google BigQuery Query Language: SQL Visualization: Tableau, Google Sheets Collaboration: Jupyter Notebooks Project 2: Aerofit Business Case Analysis Overview This project analyzes customer purchasing behaviors and product performance for a fitness company. The goal is to enhance customer segmentation and product strategy.
Key Objectives Identify customer trends based on product usage and preferences. Evaluate sales performance across different segments and regions. Provide actionable recommendations for marketing and product strategies. Highlights Customer Segmentation: Grouped customers based on usage patterns, aiding in targeted marketing. Sales Trends: Analyzed product-wise sales performance, highlighting top-performing products and regions. Retention Strategies: Provided insights to improve customer engagement and retention. Tech Stack Tools: Python (for data preprocessing), SQL Visualization: Matplotlib, Seaborn, Tableau Collaboration: Google Sheets, Jupyter Notebooks Repository Structure queries/: SQL scripts for both projects. insights/: Documented insights and recommendations. visualizations/: Graphs and charts summarizing analysis results. reports/: Final business case reports for stakeholders. Usage Clone the repository: bash Copy code git clone https://github.com/your-username/data-analysis-projects.git Navigate to the respective project folder and run the SQL scripts in your database environment. Review insights and visualizations for actionable business recommendations. Contribution Contributions are welcome! Feel free to submit pull requests or open issues for additional analysis or improvements.