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Geely Auto plans to enter the US market and produce cars locally. They’ve hired a consulting firm to identify key factors affecting car prices in the US and to determine which variables significantly impact pricing and how well they explain the price variation.
About This repository contains the Power BI project for analyzing mobile sales data. The project includes detailed visualizations and insights into key metrics to aid in decision-making. Below are the project details, including business requirements and chart specifications.
A chain of hotels, INN Hotels Group, is facing a problem of inventory loss due to booking cancellations, resulting in revenue loss. They want your help to build a Data Science solution that will help them predict the likelihood of a booking getting canceled so that they can take measures to fill in potential vacancies.
Paginated RLD Invoice Report built in Power BI Report Builder with cascading parameters and export-ready layouts.
Help an organization to improve the employee performance and improve the employee retention by creating a HR dashboard
This project aims to predict the delivery status of orders in a supply chain using historical data on orders, customer categories, product attributes, and shipping details. By developing a machine learning model, we will forecast whether an order will be delivered successfully or face delays.
The objective of this case study is to perform a comprehensive analysis of customer churn using Tableau. The analysis aims to identify patterns, trends, and factors contributing to churn, and to provide actionable insights to the company's management for implementing targeted retention strategies.
This repository features an exploratory data analysis of restaurant sales data. It involves data cleaning, descriptive statistics, and measures of dispersion, including standard deviation, skewness, and kurtosis. The goal is to uncover sales patterns and customer behavior. This project serves as a learning resource for data analysis techniques.
This repository features "Pie-in-the-Sky," a SQL-based IPL Match Bidding app. It predicts match winners, tracks team standings, and maintains bidder leaderboards. The database analyzes bidding, match, and player data, dynamically updating leaderboards based on match results.
This project is a hands-on exercise to practice data analysis techniques using Excel. The dataset consists of Airbnb rental information, used for data cleaning, exploration, and basic analysis. Key activities included handling missing values, identifying outliers, and calculating correlations.
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