I am a final-year Management Information Systems student at Lebanese University preparing for a career in data analytics and business intelligence.

I use SQL, Python, Excel, and Power BI to clean data, investigate business questions, and build dashboards that turn raw information into practical recommendations.

I ranked seventh nationwide in the Lebanese Baccalaureate in Economics and Sociology, and I bring the same discipline and attention to detail to my data projects.

Currently seeking: Data Analyst and BI Analyst internships and entry-level roles Location: Lebanon Languages: Arabic and English

• Languages: SQL, Python
• Libraries: pandas, SQLAlchemy
• Database: MySQL
• Tools: Excel, Power BI, Jupyter Notebook, Visual Studio Code
• Excel: Pivot tables, pivot charts, dashboards, XLOOKUP, slicers
• Power BI: Power Query data cleaning, data modeling, DAX measures, interactive dashboards
• Analytics: Data cleaning, exploratory data analysis, RFM segmentation, KPI dashboarding, relational data modeling

An end-to-end analysis of the UCI Online Retail II dataset using MySQL, Python, pandas, and Excel. The project covers data cleaning, sales and returns analysis, customer and product analysis, revenue concentration, country-level trends, and RFM customer segmentation. The results are presented in an interactive Excel dashboard.

Key finding: The analysis identified a 1.76% return rate on £19.66 million in gross sales, resulting in £18.93 million in net revenue.

An interactive Power BI dashboard analyzing global tech layoffs from 2020 to 2026, covering trends over time, industry breakdowns, top companies, and regional comparisons. Cleaning, data modeling, and DAX measures were all built independently within Power BI and Power Query, and the project documents data-quality limitations such as missing values and reporting inconsistencies.

Key finding: The United States accounts for the large majority of recorded layoffs in the dataset, with Retail, Hardware, and Consumer as the hardest-hit industries.

A business-focused Excel dashboard that uses KPI cards, pivot tables, charts, and slicers to analyze employee attrition and help identify where attrition risk is concentrated.

A SQL-based data-cleaning and exploratory-analysis project using hotel booking data. It examines cancellations, booking patterns, pricing, market segments, lead time, and hotel type. This project demonstrates my practical SQL and data-quality work.

• Netflix Content Analysis — Python and pandas
• Sales Data Analysis — Python and pandas
• Chinook Data Analysis — SQL and Python

I recently completed my first Power BI project and am continuing to build on it with more advanced DAX and data modeling techniques.

• LinkedIn: LinkedIn
• Email: [email protected]
• Resume: Resume