This comprehensive dataset is a goldmine for data scientists, analysts, and researchers interested in exploring a wide range of topics within the realm of online retail. It encompasses a rich collection of customer behavior and characteristics, making it a versatile resource for tackling multiple aspects of data analysis and prediction.

This project employs NLTK, Prowebscraper, and Python for sentiment analysis on online product reviews. Through web scraping, EDA, and NLP, it evaluates user satisfaction by comparing actual ratings and sentiment scores

Walmart Sales analysis, data preparation using SQL and Analyzing impact of products and customers on sales.

In this project, I have used Python & Tableau to analyse, visualize and answer business questions on Product Sales and Customer Behaviour Analysis

These dashboards provide insights across diverse domains, including cryptocurrency sales, workforce challenges, disease impact analysis, and retail trends. Leveraging tools like Power BI and Excel, they offer actionable insights for decision-making.

Bridge Health Technology - Intelligent Bridge Inspection Service Provider (Innovative Entrepreneurship Program - Product Leader)

This repository showcases the outcomes of an Exploratory Data Analysis (EDA), including visualisation, conducted on the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB and PySpark.

Group Project for Data Science for Business Project (SMU Master of IT in Business)

Dataset Northwind Mini Project Data Engineering

Google merch store sales analysis

MCS is seeking the development of an interactive Sales Dashboard to analyse and visualise sales data for our Digital, Employability, and Professional Training Courses. This project aims to empower our team with valuable insights to make data-driven decisions, optimise sales strategies, and enhance our product offerings.

The ICDE-BuyAdvisor website is a user-friendly solution to help the buyers decide whether to buy products by evaluating the product reviews for them using web scraping and machine learning techniques. Once the evaluation is completed, the product analysis is shared with the buyer.

A data-driven project analyzing product returns for three product lines (CFS, PBFS, and VFR). Machine Learning and time-series forecasting are implemented to predict return rates, identify defects, and improve supply chain efficiency.

Analysis of the behavior of computer games players

This is a comprehensive report that explores the performance of product sales and profit accross various KPIS using Power BI. This report uncovers insights and proffer reccomendations.