About project

Category:

Data Analytics | Sentiment Analysis

Tech Stack:

Python, Azure SQL, Pandas, Matplotlib, Seaborn, NLP

GitHub:

https://github.com/Nishigandha-Wankhade/Amazon-Product-Review-Performance-and-Sentiment-Intelligence/tree/main

Project Overview

Built an end-to-end data analytics and sentiment intelligence system to analyze Amazon product reviews, uncover customer sentiment patterns, and evaluate product performance using structured SQL storage and Python-based analytics.

The project combines data cleaning, SQL integration, sentiment analysis, and visualization to support data-driven product insights.

Problem Statement

Amazon product reviews contain valuable customer feedback, but raw review data is:

• Unstructured and noisy
• Difficult to analyze at scale
• Hard to convert into actionable insights

The goal was to transform raw review data into structured insights that reveal:

• Overall customer sentiment
• Product performance trends
• Rating vs sentiment alignment