Adidas Sales Report Analysis Using Power Pivot. This project focuses on analyzing Adidas' sales data using Power Pivot in Excel, showcasing key metrics to provide actionable insights for decision-making. The public dataset was extracted, cleaned, and transformed in Power Pivot to create the following KPIs: Sales by Region – Analyzed total sales by geographical regions. Sales by Retailer – Measured sales contribution from different retailers. Sales Performance – Tracked sales growth over time. Sales by Product – Identified top-selling products. Sales by City – Assessed sales distribution across various cities. Sales by Channel – Compared online vs. offline sales performance. Total Customers – Counted unique customers. Total Units Sold – Summed the total number of units sold. The interactive dashboard was built using Pivot Tables, offering a dynamic view of Adidas' business performance. This project demonstrates my data analysis, Power Pivot, and visualization skills.

e-Trade Pharmaceutical Company Report Using Power Pivot This project involves analyzing sales and commission data for a pharmaceutical company, e-Trade, using Excel Power Pivot. The data was extracted, cleaned, and modeled to generate insights from the following KPIs: Revenue by Country – Analyzed revenue contribution from each country. Revenue by Company – Assessed revenue generated by different pharmaceutical companies. Sales by Quantity – Tracked sales volume across all regions. Commission to External Agents by Country – Measured agent commissions by country. Commission to External Agents by Company – Evaluated commissions based on company partnerships. Sales by Brand – Identified top-selling pharmaceutical brands. Total Sales – Summed total revenue across all channels. Total Quantity Sold – Calculated total units sold. Total Agent Commission – Aggregated commissions paid to external agents. This interactive dashboard was built to display these KPIs, providing a comprehensive view of company performance.

Call Center Analysis Report Using Power Pivot This project analyzes customer inquiry data for a call center using Excel Power Pivot. The data was extracted, cleaned, and modeled to deliver key performance insights through the following KPIs: Customer Inquiry by Call Center – Analyzed inquiries received via phone calls. Customer Inquiry by Chatbot – Measured inquiries handled by chatbots. Customer Inquiry by Email – Tracked inquiries received through email. Customer Inquiry by Web – Assessed inquiries from the web portal. Calls by Sentiment – Classified calls based on customer sentiment (positive, neutral, negative). Total Inbound Calls – Calculated total inbound customer calls. Calls by State – Broke down calls by geographic location. This project demonstrates my skills in data analysis and Power Pivot modeling.

Bike Sales Analysis Report Using Power Pivot This project focuses on analyzing bike sales data using Excel Power Pivot. The dataset was extracted, cleaned, and analyzed to generate insights through the following KPIs: Sales by Average Income – Analyzed sales distribution based on customer income levels. Sales by Age Bracket – Evaluated sales trends across different age groups. Sales by Marital Status – Assessed how marital status influences bike purchases. Sales by Region – Measured sales across various geographical regions. Sales by Gender – Tracked bike sales by customer gender. An interactive dashboard was built to visualize these KPIs, providing actionable insights into customer demographics and regional sales performance. This project highlights my ability to leverage Power Pivot for data-driven decision-making..