Analytics & Visualization

In a comprehensive examination of road accident data across England, this analysis sheds light on the factors and patterns driving incident rates on the roads. From identifying peak accident times to uncovering correlations between accident severity and weather conditions, the findings reveal key insights into road safety. The project leverages statistical tools and visualizations to present a data-driven perspective on how, when, and where road incidents are most likely to occur, informing strategies for safer travel. 

Uncover the numbers behind the Indian Premier League with this interactive Power BI analysis! From Title Winners to Orange and Purple Cap holders, explore the Key Performance Indicators that define the game’s elite players. Dive deeper into batting and bowling stats, toss decisions, and team performance by match results. This project offers a thrilling breakdown of the IPL’s high-energy moments and player achievements, bringing every boundary, wicket, and win into focus. 

Discover the story behind Zomato’s sales performance! This analysis dives into order amounts, annual sales, customer demographics, and user ratings to reveal what drives customer loyalty and influences sales trends. From tracking growth to identifying key patterns, it’s a comprehensive view of Zomato’s business dynamics. 

This dashboard analyzes global COVID-19 case data from the first six months of the pandemic using Tableau, tracking confirmed and death cases across countries. It visualizes key indicators like overall case counts, case trends, and top impacted countries. The project offers an at-a-glance understanding of how the virus spread during the initial wave. 

Explore the financial pulse of a leading US-based superstore through Tableau! This analysis covers nationwide sales, profit margins, and discount patterns, showcasing the balance between sales and profit. Dive into interactive maps, distribution trends, and key sales insights to get a clear view of the store’s performance across regions. 

Using exploratory data analysis on hotel booking data, this project examines cancellation trends and seasonal sales patterns to uncover which hotels and booking types are most affected. Insights from the analysis reveal when cancellation rates spike and provide actionable suggestions to improve booking reliability and hotel performance.