Projects using Microsoft Power BI in Pune
Projects using Microsoft Power BI in Pune
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Sunny Mehta
Marketplace Profitability & P&L Engine Overview This project is an end-to-end E-commerce Marketplace Analytics solution built using MySQL, SQL, Power BI, and Excel. The objective of this project is to analyze marketplace profitability across multiple sales channels by calculating revenue, product costs, marketplace commissions, shipping expenses, and net profit. The project simulates a real-world marketplace operations environment where business teams need visibility into product performance, marketplace profitability, and operational KPIs. Business Problem E-commerce businesses often track revenue but fail to understand true profitability. This project helps answer key business questions: Which marketplace generates the highest profit? Which products are most profitable? How do commissions impact margins? What is the overall profit margin? How does shipping cost affect profitability? Tech Stack MySQL SQL Power BI Microsoft Excel Data Sources Products Contains SKU-level product information. Fields: SKU Product Name Category Cost Price Selling Price Orders Contains marketplace order transactions. Fields: Order ID Order Date Marketplace SKU Quantity Marketplace Charges Marketplace commission structure. Fields: Marketplace Commission Percentage Shipping Cost Shipping cost by marketplace. Fields: Marketplace Shipping Cost Returns Order return information. Fields: Order ID Return Status SQL Implementation The project uses multiple SQL tables and joins to create a unified profitability dataset. Key SQL Concepts Used: CREATE TABLE INNER JOIN SQL Views Aggregations Calculated Metrics A consolidated analytical view was created: vw_marketplace_pnl This view combines all business logic and serves as the primary source for Power BI reporting. Profitability Metrics Revenue Revenue = Quantity × Selling Price Product Cost Product Cost = Quantity × Cost Price Commission Cost Commission Cost = Revenue × Marketplace Commission % Shipping Cost Shipping Cost = Quantity × Shipping Cost Profit Profit = Revenue − Product Cost − Commission Cost − Shipping Cost Profit Margin % Profit Margin % = Profit / Revenue Power BI Dashboard Executive Summary KPIs: Total Revenue Total Profit Total Orders Profit Margin % Marketplace Analysis Revenue by Marketplace Profit by Marketplace Marketplace Performance Comparison Product Analysis Top Profitable Products Product Revenue Analysis Product Profitability Ranking Trend Analysis Revenue Trend Profit Trend Order Trend Project Architecture Excel → MySQL → SQL View → Power BI Dashboard Key Outcomes Built a scalable marketplace profitability model. Centralized business logic using SQL Views. Automated profitability calculations. Delivered interactive executive dashboards for decision-making. Simulated a real-world marketplace operations analytics workflow. Skills Demonstrated SQL Data Modeling Business Intelligence Power BI E-commerce Analytics Marketplace Operations Profitability Analysis Data Visualization Author Sunny Mehta Open to opportunities in: E-commerce Operations Marketplace Management Business Analytics Operations Analytics Data Analytics
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Smita S
MRR & Churn Analysis Dashboard for SaaS Retention and Growth
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Rohit Poddar
Credit Card Spending Pattern and Customer Acquisition | Power BI
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Umesh Joshi
GTM_EMEA_Software_Sales🚀
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Sarbjot Singh
Data Analytics Project | BlinkIT Grocery Sales Analysis Excited to share my latest Data Analytics project ,where I analyzed BlinkIT Grocery Sales Data and delivery data to uncover meaningful business insights 📈 📊 What I worked on: Analyzed sales performance across product categories, outlet types, sizes, and locations Identified top-performing item categories and customer preferences Studied the impact of outlet size, establishment year, and visibility on sales Converted raw data into actionable insights and business recommendations 💡 Key Insights: Fruits & Vegetables, Snack Foods, and Frozen Foods drive maximum sales FOR FULL PROJECT VIST GIT HUB –( https://lnkd.in/d34sdAPz )
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Riya Mota
Microsoft Fabric Project - End-to-End Analytics Solution with Microsoft Fabric - Developed an end-to-end analytics solution using Microsoft Fabric, including Lakehouse, Notebooks, Pipelines, and semantic models to automate data ingestion and reporting workflows.
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VARSHA ZOKE
Cricket WorldCup Dashboard
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Ateeb Mahedvi
HR Analytics Dashboard
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Amal Jose
Developed an interactive Amazon Product Analytics Dashboard in Power BI to analyze 200+ product categories, pricing trends, discount effectiveness, customer ratings, and performance drivers. Leveraged Power Query, DAX, and advanced visualizations to transform raw e-commerce data into actionable business insights, enabling data-driven pricing and product strategy decisions.
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Daniyal Shaikh
Online Retail Price Analysis - Flipkart vs Amazon
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Aishwarya Mahajan
Responsive Sales Dashboard for Madhav Store
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Neha Madrala
Data is useless. Yes, it is. Because on its own, it doesn’t say much. It’s just numbers, rows, and columns. The real value comes when that data is understood — when it answers a question, shows a pattern, or drives a decision. That’s what turns data into information. And that’s what businesses actually need.
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Weitblick
Real Estate Power BI Dashboard
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saikat nandi
Sales Analysis E-Commerce Power BI
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Jash Joshi
Enhancing Operational Efficiency through ETL Solutions
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Siddhartha Tiwari
Adidas Report - Sample
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