Hospital database system built with Oracle APEX and SQL, featuring an interactive dashboard for real-time insights into patient distribution and doctor availability. Designed to optimize resource management and support hospital administration in data-driven decision-making.

Advanced Excel dashboard designed to analyze product category performance and provide interactive insights into monthly sales trends. Uses tools like regression analysis and combo boxes to enhance decision-making with key metrics on sales and profit.

A time series forecasting project using ARIMA and Python to predict Netflix’s quarterly subscription growth, aiding data-driven decisions in content strategy and business planning.

This project presents an interactive Power BI dashboard for analyzing Blinkit sales performance across multiple dimensions such as product categories, outlet size, fat content, and year-wise trends.

Premier Data Scout - CETYS MBA 2025

Modeling Agri-finance Credit Risk with Data & Machine Learning using Python (Jupyter Notebook)

Data-driven analysis inspired by the Moneyball approach, identifying affordable replacements for key Oakland A's players using R and sabermetrics to support cost-effective recruitment.

This repository contains materials for a Data Analysis Hackathon I designed to provide learners with practical experience in analyzing e-commerce sales and customer insights. Participants utilize tools such as Excel, SQL, Python, and Power BI to explore datasets, uncover trends, answer key business questions, and generate actionable insights.

This project is a comprehensive Power BI dashboard that analyzes **sales performance**, **revenue trends**, and **profit margins** across multiple markets and years. It provides interactive insights to help stakeholders understand how different regions, products, and customers contribute to overall business performance.

Developed an interactive Power BI dashboard by integrating transaction and customer data from a SQL database to provide real-time insights. Streamlined data processing to monitor key performance metrics and trends, sharing actionable insights with stakeholders to support data-driven decision-making.

This project involves data cleaning and exploratory data analysis (EDA) of a fictional retail clothing store dataset. The focus of this analysis is to identify trends, correct inconsistencies, and derive insights in order to make data-driven decisions.

A data-driven approach to designing an optimal Data Science curriculum. This project extracts skills from job postings, applies NLP and clustering techniques (K-Means, Hierarchical, DBSCAN), and maps industry demands to educational recommendations. Uses Python, Scikit-learn, OpenAI embeddings, and Seaborn for visualization.

This project uses vehicle auction data to identify key factors affecting sale prices and auction timelines, uncovering insights and strategies to optimize auction efficiency, inventory management, and overall sales performance.

A Python script to analyze sales performance using Pandas and Matplotlib. Loads, cleans, and visualizes sales data, calculating key metrics (total sales, average order value, unique customers) and generating trends (monthly sales, product category performance). Includes error handling for robust execution.

The Hospitality-Domain-Project is a Power BI dashboard for AtliQ Grands, enabling them to track key metrics, make data-driven decisions, and achieve a 20% efficiency boost and 15% revenue growth.

This repository contains a Power BI dashboard designed to analyze Amazon's global sales performance. It provides dynamic, interactive visualizations of sales by region, segment, and customer, helping to uncover insights and guide data-driven business decisions.

SQL project analyzing customer responses to a marketing campaign

This project analyzes AtliQ Grands' hotel revenue, occupancy trends, and profitability using Power BI. The interactive dashboard provides insights into RevPAR, ADR, market share, and customer behavior to help the management make data-driven decisions. 🔗 Live Power BI Dashboard

This interactive dashboard assesses supplier risk by integrating performance metrics (on-time delivery, quality scores) with a real-time geopolitical risk score derived from NLP-based news sentiment analysis. The goal is to provide supply chain managers with a proactive tool to mitigate disruptions.

Tableau de bord R Shiny pour le monitorage du développement professionnel en établissement scolaire, intégrant une récolte de données via LimeSurvey et des visualisations dynamiques par profil utilisateur (enseignant, direction, chercheur).