Mohammad Khairy Rashad Fadel — Data Analyst Power BI Developer

Challenge: The core challenge was to analyze end-to-end sales and shipping operations for an online store ($2.0M Total Sales across 5,009 orders) to identify key drivers of profitability and shipping bottlenecks. The primary objectives were to evaluate if heavy discounting strategies genuinely increased sales or merely eroded profit margins, pinpoint region-specific shipping delays, and identify top-performing product categories to optimize business growth

Process: I applied an end-to-end data analytics workflow using Power Query, DAX, and Power BI:Data Cleaning & Preparation: Used Power Query to handle missing values, structure order data, and achieve 100% data accuracy. Data Modeling: Modeled a scalable Star Schema linking sales, products, customers, location, and a custom date dimension (dim_date) to optimize performance and slicer filtering. DAX Analysis & Measures: Authored custom DAX measures to track essential financial KPIs, profit margins (e.g., Technology at 20%), discount distribution ($323K total discounts), and average shipping latency across states.

Solution: I designed an interactive Power BI dashboard structured into strategic narrative sections:Financial Growth & Regional Insights: Visualized a 55% 4-year growth rate and regional breakdowns, showing the West region as the primary revenue generator ($632.1K). Product & Customer Profiling: Highlighted top-tier products like the Canon imageCLASS ($25.2K profit) and key VIP accounts like Tamara Chand ($19.0K sales). Discount & Operational Auditing: Analyzed discount efficiency against sales volumes and tracked shipping latency state-by-state, identifying major shipping bottlenecks (e.g., District of Columbia averaging a 6-day delay vs. the 4-day overall average).

Outcome: Key Results & Business Impact:Financial Clarity: Evaluated $2.0M in total sales and $286K in net profit. Identified that Technology is the most lucrative category with a 20% profit margin, while Office Supplies saw heavy discounting ($76K in discounts for 22.9K units) with minimal margin gain. Operational Optimization: Identified shipping bottlenecks (District of Columbia leading at 6 days latency), leading to actionable recommendations to adjust local logistics partners. Strategic Recommendations: Proposed cutting aggressive discounts on low-margin items to instantly boost net profitability, launching a VIP loyalty program for top accounts, and expanding high-margin technology inventory.

Challenge: The primary goal was to analyze e-commerce sales, orders, and customer behavior for Olist Store in Brazil to uncover strategies for lowering shipping costs and increasing overall profitability. The core challenge involved answering key business questions, such as whether high shipping costs deter purchases in certain states and identifying the payment methods customers prefer most.

Process: I utilized a comprehensive data pipeline and tech stack to manage the analysis:Data Ingestion & Pipeline: Leveraged Python scripts to efficiently extract raw datasets and automate the data transfer process directly into the database.Database Management: Used PostgreSQL to securely store and manage millions of sales records. Data Cleaning: Employed Power Query to clean the dataset and properly link customer and product lists. Data Modeling & DAX: Built intelligent formulas (Measures) using DAX to track critical KPIs like yearly growth. Visualization: Designed interactive dashboards using Power BI to turn complex data into easily readable charts.

Solution: I developed a structured Power BI dashboard that provided a holistic view of the store's operations. The solution tracked 96K total customers across 27 states, mapping regional sales distribution (such as São Paulo leading with $5.0M in sales), monitoring delivery speeds across different regions, and analyzing product quality (averaging a 4.0/5.0 rating) alongside payment behaviors.

Outcome: Financial Impact: Evaluated a robust $14M in total sales across 113K orders, demonstrating a 24.88% Year-over-Year (YoY) growth and an Average Order Value of $154.10. Logistics Insights: Discovered that shipping costs above $50 caused order volumes to drop by more than 90%, whereas medium-priced shipping ($11–$25) drove the highest volume. Pinpointed major delivery delays in states like Amapá (27 days) and Amazonas (23 days) against a 6-day national average. Strategic Action Plan: Recommended partnering with local couriers to fix slow delivery states, offering "smart free shipping" to boost medium-cost tiers, reallocating 60% of the marketing budget to top-selling categories (like Health & Beauty at $1.3M), and incentivizing credit card usage (already at 73.92%) with a 1-2% discount to reduce bank slip dependency