I specialize in transforming complex data into clear insights that drive informed business decisions. As a skilled Data Analyst, I have hands-on experience in data cleaning, visualization, interactive dashboard creation, and machine learning. My expertise allows me to extract meaningful insights from raw data, enabling data-driven strategies and solutions. My skills include: ✔ Excel ✔ Python (NumPy, Pandas, Matplotlib, Seaborn, Sklearn) ✔ Data Visualization: Power BI, Tableau ✔ Data Processing & Cleaning ✔ SQL Server ✔ Web Scraping ✔ Machine learning (including algorithms, e.g., Decision Tree, K-Nearest Neighbour, Random forests, etc.) Projects & Experience: I have successfully applied my skills to various projects, including: • Toy Store E-commerce Analysis • Coffee Beans Analysis • Hospitality Dashboard • HR Analytics Dashboard • Pizza Sales Analysis • Loan Approval Prediction • House Price Prediction • Customer Churn Analysis Check out the full project's implementation on GitHub: [_Website not available. Sign in: https://www.twine.net/signup_ I am excited to collaborate with you and transform your data into valuable business insights.…

Marvel Baheeg

I specialize in transforming complex data into clear insights that drive informed business decisions. As a skilled Data Analyst, I have hands-on experience in data cleaning, visualization, interactive dashboard creation, and machine learning. My expertise allows me to extract meaningful insights from raw data, enabling data-driven strategies and solutions. My skills include: ✔ Excel ✔ Python (NumPy, Pandas, Matplotlib, Seaborn, Sklearn) ✔ Data Visualization: Power BI, Tableau ✔ Data Processing & Cleaning ✔ SQL Server ✔ Web Scraping ✔ Machine learning (including algorithms, e.g., Decision Tree, K-Nearest Neighbour, Random forests, etc.) Projects & Experience: I have successfully applied my skills to various projects, including: • Toy Store E-commerce Analysis • Coffee Beans Analysis • Hospitality Dashboard • HR Analytics Dashboard • Pizza Sales Analysis • Loan Approval Prediction • House Price Prediction • Customer Churn Analysis Check out the full project's implementation on GitHub: [_Website not available. Sign in: https://www.twine.net/signup_ I am excited to collaborate with you and transform your data into valuable business insights.…

Available to hire

I specialize in transforming complex data into clear insights that drive informed business decisions. As a skilled Data Analyst, I have hands-on experience in data cleaning, visualization, interactive dashboard creation, and machine learning. My expertise allows me to extract meaningful insights from raw data, enabling data-driven strategies and solutions.

My skills include:
✔ Excel
✔ Python (NumPy, Pandas, Matplotlib, Seaborn, Sklearn)
✔ Data Visualization: Power BI, Tableau
✔ Data Processing & Cleaning
✔ SQL Server
✔ Web Scraping
✔ Machine learning (including algorithms, e.g., Decision Tree, K-Nearest Neighbour, Random forests, etc.)

Projects & Experience:
I have successfully applied my skills to various projects, including:
• Toy Store E-commerce Analysis
• Coffee Beans Analysis
• Hospitality Dashboard
• HR Analytics Dashboard
• Pizza Sales Analysis
• Loan Approval Prediction
• House Price Prediction
• Customer Churn Analysis
Check out the full project’s implementation on GitHub: [Website not available. Sign in: https://www.twine.net/signup

I am excited to collaborate with you and transform your data into valuable business insights.

See more

Skills

Experience Level

Microsoft Excel
Expert
Data Visualization
Expert
SQL
Expert
MySQL
Expert
Python
Expert
Data Science
Intermediate
Power BI
Intermediate

Language

English
Intermediate
Arabic
Fluent

Work Experience

Add your work experience history here.

Education

Bachelor of Computer and Artificial Intelligence at Sohag University
September 20, 2019 - June 20, 2024
During my studies at the Faculty of Computer and Artificial Intelligence, I gained a strong foundation in programming, data structures, algorithms, databases, and artificial intelligence concepts. I learned how to analyze problems logically and design efficient solutions using computational thinking. I also developed practical skills in data analysis, machine learning, and artificial intelligence, working with real datasets and applying theoretical knowledge to real-world scenarios.

Qualifications

Add your qualifications or awards here.

Industry Experience

Computers & Electronics
    paper Pizza Sales Analysis

    This project analyzes a pizza restaurant’s historical sales data to uncover key business insights using Excel, SQL queries, and Power BI tools. The goal is to evaluate overall performance, understand customer ordering behavior, and identify product trends that influence revenue. The dataset used in this project is the Pizza Sales Dataset from Kaggle.

    🔗 Source: https://www.twine.net/signin

    Key Business Questions Answered:
    Which pizza category generates the highest sales?
    Which pizza size receives the most customer orders, and which size performs the least?
    What are the top 5 best-selling pizzas, and which are the bottom 5 lowest-selling pizzas?
    Which month and quarter recorded the highest sales performance?
    During which time of day do sales peak?

    Key Insights:
    Total Revenue: 817K
    Total Orders: 21K
    Total Pizza Sold (Quantity): 50K
    Average Order Value (AOV): 38.31

    paper Toy Store E-commerce Analysis

    This Project analyzes an E-Commerce Toy Store dataset from [Maven Analytics] (https://www.twine.net/signin It is designed to help businesses understand purchaseing pattern, Customer behaviour, and website performance.

    Tools Used:
    SQL Server: Transformation and Analysis
    Power BI: Data modeling + Dashboard
    Github: Project documentation & version control

    Key Business Questions Answered:
    What are the Total Revenue and the Average Order Value (AOV), both overall and broken down by year?
    Which product generates the highest sales?
    What is the refund rate for each product?
    What is the customer conversion rate?
    Which marketing channels bring the most customers?
    Which campaign brings in the most customers?
    What devices (mobile/desktop) convert better?
    Which products are the customer’s primary choices and which are not?

    Key Insights:
    Total Revenue: 1.94M
    Average Order Value (AOV): 59.99
    Total Orders: 32K
    Refund Rate: 4.40%
    Best-selling Product: The Original Mr. Fuzzy
    Top Traffic Campaign: “nonbrand” = 23K
    Top Traffic Platform: “gsearch” = 21K
    Conversion Rate: 6.83%
    Device Performance: Desktop (86.05% - 28K), Mobile (13.95% - 5K)
    Repeated Visitors: about 6K

    Check out the full project implementation on GitHub: [https://www.twine.net/signin

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