Tarek Nageh

The data analysis highlighted significant performance variance across regions and a sharp sales drop in 2016 following a 2015 peak. I utilized DAX functions to create dynamic time-intelligence calculations (like Quarter-over-Quarter) and implemented interactive data visualization techniques to allow managers to instantly filter sales trends, identify low-performing states, and strategize for future growth. This comprehensive Sales Analysis Dashboard turns raw transaction data into clear, actionable insights for executive teams.

The data analysis focuses on departmental distribution (Manufacturing is largest), gender ratios (mostly male, 65%), and geographical distribution (Main center has the largest headcount of 251). I employed advanced filtering and data visualization to highlight the peak headcount period in 2019, enabling HR leaders to better understand employee trends, plan recruitment strategies, and manage compensation and workforce efficiency effectively. The dashboard includes interactive slicers for dynamic filtering by department, location, and time period.

The analysis integrates Sales, Profit, and Detailed Item Metrics across three interconnected dashboards (Sales, Profit, and Details). Key features include: tracking high sales ($62.7K), maximum profit ($3.1K), dynamic filters by Branch and Geographic Segment, and a deep-dive table showing profitability by product category (Smartphones/Tablets) in each branch. The use of Excel's power features including Pivot Tables, Power Query, and advanced formulas ensures real-time, actionable insights for strategic decision-making and performance monitoring.

The dashboard analyzes 512 passed students with detailed breakdowns by 5 major courses: Literature Survey (209 students), Computer Science 101 (208), History of Art (202), Statistics for Beginners (194), and Introduction to Biology (187). Category analysis reveals Fiction leads with 231 students (23.1%), followed by Science Fiction 206 (20.6%), Mystery 202 (20.2%), Romance 183 (18.3%), and Non-fiction 178 (17.8%). Geographic distribution covers USA, Canada, Brazil, UK, France, Germany, Spain, Italy, India, Japan, and Australia. The system tracks 2.50 average rating with YOY growth analysis from 2010-2021.

Developed comprehensive SQL queries to analyze retail sales data, focusing on revenue trends, customer behavior, and product performance. Created complex joins, aggregations, and window functions to derive actionable insights from transactional data. Implemented data cleaning and transformation techniques to ensure data quality and consistency. Generated key performance indicators (KPIs) including monthly sales growth, customer retention rates, and product category rankings. The project demonstrates proficiency in SQL Server, MySQL, and database optimization techniques for large-scale data analysis.