An interactive Retail Sales Performance Dashboard built using Microsoft Excel, featuring KPIs, Pivot Tables, Pivot Charts, XLOOKUP, and Slicers for business insights.
The HR Employee Attrition dataset contains employee information used to analyze why employees leave a company. It includes details such as age, department, salary, job role, overtime, job satisfaction, and work-life balance. The dataset helps organizations understand employee behavior, improve retention strategies, and make better HR decisions.
SQL analysis of the Global Superstore Sales dataset using SQLite to answer business questions and extract actionable insights.
A minimal data analytics project identifying profit leakage drivers using Python and Power BI
Restaurant Data Analysis using Python | Data Cleaning, EDA & Business Insights
Data analysis comparing Adidas and Nike products based on price, ratings, discounts and customer engagement.
End-to-end data analysis project using SQL & Power BI, covering sales performance, customer insights, and inventory risk analysis.
SQL-based business performance analysis focused on KPIs, sales trends, profitability, customer performance, and actionable business insights.
End-to-End Amazon Sales Analysis using Python, Pandas, NumPy, Matplotlib, and Seaborn with EDA, business insights, and data visualizations.
An open platform for exploring retail data, discovering trends, and supporting data-driven business decisions.
Financial fraud detection using Python and Machine Learning with EDA, SMOTE, feature engineering, and classification model evaluation.
(Graduation Project) AI-powered business planning platform — analyze markets, score opportunities, manage projects, and chat with an AI consultant in English or Arabic
Machine Learning project to classify and predict Tesla stock risk categories using KNN, Decision Tree, SVM and Random Forest.
This project analyzes customer reviews from Amazon to uncover patterns in customer satisfaction, sentiment trends, and behavioral insights over time. The goal is to transform raw textual data into meaningful business insights that can support decision-making and improve customer experience.
Sales, profitability and inventory analysis using Pandas and Power BI.
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