🛒Amazon Product Data Analysis

📊Dataset Overview

• 🆔Product Details:
  • Product ID
  • Name
  • Category
  • Discounted Price
  • Actual Price
  • Discount Percentage
• ⭐Customer Ratings and Reviews:
  • Rating
  • Rating Count
  • Review ID
  • Review Title
  • Review Content
  • User ID
  • User Name
• 📷Additional Information:
  • Product Image Link
  • Product Link
  • Product Description

🎯Key Objectives and Queries

1. 🥇Identifying the highest-rated products and those with the largest discounts.
2. 💸Analyzing pricing trends across categories, including average, minimum, and maximum prices.
3. 📈Exploring customer review patterns, such as the number of reviews per product and the average rating by category.
4. 🌟Detecting the most popular products based on rating counts and reviews.
5. 📉Calculating average discounts and evaluating how discount percentages correlate with product ratings and review counts.
6. 📝Investigating product descriptions and user feedback to find common keywords or phrases related to high ratings.

💡Skills Demonstrated

• 🗃️SQL Querying: Advanced filtering, grouping, sorting, and aggregation techniques.
• 🔍Data Investigation: Extracting and interpreting trends in pricing, discounts, and user ratings.
• 📊Data Visualization & Reporting: Translating SQL results into meaningful visualizations and summaries for business insights.
• 🧩Analytical Problem-Solving: Leveraging SQL for complex, real-world data analysis challenges.

🔎Insights and Outcomes

• The analysis provides valuable insights into Amazon product trends and customer feedback, offering data-driven recommendations to optimize product listings, pricing strategies, and promotional discounts.