Advanced SQL Analytics Project

📌 Overview

This project demonstrates how SQL can be used as a complete analytics tool — from raw data exploration to advanced analysis and final business reporting.

The workflow covers:

• EDA (Exploratory Data Analysis)
• ADA (Advanced Data Analytics)
• Data transformations
• Final analytical reports for Customers and Products

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📂 Project Structure

• 📁 datasets/ – Raw datasets used for analysis
• 📁 sql_scripts/ – SQL scripts for EDA, ADA, and transformations
• 📁 assets/ – Report screenshots (Customer & Product)
• 📄 README.md – Project documentation

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🔍 Methodology

1. Exploratory Data Analysis (EDA)

   • Profiled datasets, identified missing values, duplicates, and outliers.
   • Summarized sales distributions, seasonal trends, and customer/product activity.

2. Advanced Data Analytics (ADA)

   • Implemented window functions (running totals, rankings, moving averages).
   • Created cumulative sales, period-over-period (MoM/YoY) comparisons, and segmentation.
   • Built customer and product performance metrics.

3. Transformations & Reports

   • Cleaned and standardized data using modular SQL scripts.
   • Built two final SQL views:
     • Customer Report View – customer-level KPIs (revenue, order frequency, trends).
     • Product Report View – product-level KPIs (sales volume, revenue trends, rankings).

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📊 Final Reports

🧑‍🤝‍🧑 Customer Report

📦 Product Report