The Customer Churn Analysis Dashboard is an interactive tool designed to provide deep insights into customer behavior and identify key factors driving customer churn. By leveraging comprehensive customer metrics, billing details, and subscription patterns, this dashboard empowers data-driven decision-making aimed at reducing churn rates and enhancing customer retention strategies.

This dashboard provides an in-depth analysis of employee demographics, performance, and distribution within Pharma Group AG. It encompasses various metrics such as age distribution, gender-based hiring, performance levels, time to promotion, job roles, regional distribution, and average ratings.

This dashboard provides a comprehensive overview of the export activities of India, including metrics related to the value and count of exported commodities, yearly trends, top export destinations, and a detailed analysis of the exported commodities.

This project involves an in-depth analysis of the Car Dekho dataset using SQL. The dataset comprises information about various cars, including their names, years, and fuel types. The project aims to uncover trends and patterns in car availability over the years, categorize cars based on fuel types, and examine the availability of cars in specific years. The analysis provides valuable insights into the car market, helping understand the distribution of cars over time and fuel preferences.

This project involves a comprehensive analysis of the retail store dataset using SQL. The dataset consists of transaction information, including sale dates, times, customer demographics, categories, quantities, and sales values. The goal of the project is to explore and analyze sales data to identify trends, customer behavior, and sales performance across different categories and time periods. The analysis provides valuable insights into the retail store's operations, helping to understand customer preferences and optimize sales strategies.

This project entails a thorough analysis of the Netflix dataset using Pandas. The dataset includes information about titles, genres, release dates, durations, and ratings. The objective is to uncover viewing trends, popular genres, release patterns, and user ratings. The analysis aims to provide valuable insights into Netflix's content library and viewer preferences, helping to understand what makes content popular on the platform.

This Python-powered project focuses on in-depth data analysis and visualization using Pandas, Matplotlib, and Seaborn. It explores trends, patterns, and insights from a comprehensive cars dataset, covering aspects like pricing, engine performance, fuel efficiency, and transmission types. Through efficient data cleaning, manipulation, and visualization, it showcases proficiency in Python programming and storytelling through data-driven insights.

This project involves a detailed analysis of e-commerce sales data using an Excel dashboard. The dashboard provides various visualizations and metrics to understand sales trends, customer demographics, product performance, and payment methods. The goal is to provide valuable insights into the e-commerce business, helping to optimize sales strategies and improve customer experience.

This project involves creating an Excel dashboard to analyze and compare statistics across different continents. The dataset includes information on population, area, growth rates, and world coverage for each continent. The goal is to visualize key metrics and trends to provide insights into demographic and geographic characteristics of continents.