Calculated and analyzed the key metrics of Hospitality data using My SQL.

Using Python Analyzing hospitality data to optimize operations, enhance customer experience, and boost revenue. Focus areas: occupancy trends, personalized services, pricing strategies, and risk management. Tools: Python (Pandas) and EDA. Enabling data-driven decisions for business success.

Customer loyalty segmentation & strategic recommendations using SPSS discriminant analysis to boost retention and competitive positioning at Shiva Tourist Dhaba.

An end-to-end Power BI Business Intelligence solution for the hospitality industry. Features dynamic DAX measures for Revenue (RevPAR, ADR) and interactive tooltips to drive data-driven decision-making for hotel managers.

This repository contains a project for analyzing hospitality industry data. It includes an SQL script for data analysis, raw data in Excel format, and a Tableau dashboard preview. The project provides insights into key metrics like revenue, occupancy, and booking trends.

Exploratory Data Analysis: Projet d'analyse des offres d’hébergement de Booking.com et d’autres sources, incluant collecte de données, nettoyage, modélisation prédictive et tableau de bord interactif.