E Commerce Data Analysis Readme Md At Main Github

There was an error while loading. Please reload this page. An open API service indexing awesome lists of open source software. E-Commerce real world example of run-aspnetcore ASP.NET Core web application. Implemented e-commerce domain with clean architecture for ASP.NET Core reference application, demonstrating a layered application architecture with DDD best practices. Download 100+ page eBook PDF from here -> https://github.com/aspnetrun/run-aspnetcore-realworld

aspnet-core aspnet-core-template aspnetcore aspnetcore-basic-authentication aspnetcore-httpcontext aspnetcore-identity authentication authorization bootstrap4 business-rules clean-architecture configuration ddd-architecture ecommerce entity-framework-core multipage-application razor-pages real-world-project shopping-cart validation Last synced: 8 months ago JSON representation E-Commerce real world example of run-aspnetcore ASP.NET Core web application. Implemented e-commerce domain with clean architecture for ASP.NET Core reference application, demonstrating a layered application architecture with DDD best practices. Download 100+ page eBook PDF from here -> Business Intelligence Developer | Data Analyst | SQL Developer | Power BI & Excel Reporting | Turning Data into Insights

🚀 Excited to share my latest Excel Dashboard Project — FreshMart Sales Insights Dashboard! The focus of this project was to take raw data from FreshMart Store and transform it into an interactive, insight-driven tool that helps decision-makers analyze performance with just a few clicks. 🛠 Tools & Techniques in Excel: Power Query → Automated data cleaning & preprocessing Power Pivot → Data modeling & calculated measures Pivot Tables & Pivot Charts → Interactive, filter-responsive analysis GETPIVOTDATA → Dynamic... Delivery Time: 24.36 mins | On-Time Rate: 76.08% • September Peak: 4,231 orders generating $1.213M • Organic channel drove most sales 🧠 This project strengthened my Excel modeling, data storytelling, and KPI design skills... 🔗 Explore full project on Github : https://lnkd.in/g6kxKiBf #ExcelDashboard #DataAnalytics #DataVisualization #ExcelSkills #PortfolioProject #Analytics #BusinessIntelligence #Excel #PowerQuery #PowerPivot #DataAnalytics #DataAnalysis #SalesAnalytics #DashboardDesign #InteractiveDashboard #ExcelCommunity #ExcelTips #DataVisualization #DataDriven #DataStorytelling #MicrosoftExcel #AnalyticsDashboard #Reporting #BI #ExcelProjects #DataModelling... Experienced Audit and Banking Professional | Transitioning into Data Analytics to Power Business Growth

🚀 Blinkit Sales & Regional Performance Dashboard – Power BI Project Thrilled to share my latest Power BI dashboard designed to analyze Blinkit’s sales performance across outlets, regions, and product categories. 🔍 Project Overview: This dashboard provides a centralized view of KPIs — Total Sales, Average Sales, Ratings, and Item Counts — helping management make data-driven decisions. It explores performance variations across outlet tiers, establishment years, and item attributes like fat content and product type. 💡 Tech Stack Used: Power BI Desktop | Power Query (M Language) | DAX | CSV/Excel | Git & Git LFS 📊 Dashboard Highlights: $96.3K Total Sales | 3.3 Avg. Rating | 35 Items Outlet Size & Tier Insights: Tier 1 outlets lead with $96K in total sales Sales Trend Analysis: Peaks in 2015 & 2021 Top Categories: Snacks, Soft Drinks & Breakfast items... 💻 Explore More: 🔗 View Dashboard: https://lnkd.in/g8VHDiUe 💻 GitHub Repository: https://lnkd.in/gm83gxHW 🌐 Portfolio: https://lnkd.in/gMqdrHWT Would love your thoughts or suggestions to make it even better!

🙌 #PowerBI #DataAnalytics #DashboardDesign #Blinkit #BusinessIntelligence #MicrosoftPowerBI #DataVisualization #AnalyticsProject #GitHubProjects #Portfolio #DataDriven Aspiring Data Analyst | Data Science | B.Tech | Python | SQL • Tableau • R • Excel | EventScape @ GDGoC IPSA | Google Cloud Arcade | Author @ Guru Shishya Publications |... There was an error while loading. Please reload this page. There was an error while loading. Please reload this page.

There was an error while loading. Please reload this page. This project focuses on analyzing and managing data for an e-commerce platform. The objective is to build insights into customer behavior, product performance, and operational efficiency. The project uses SQL for data handling, Python (via Jupyter Notebook) for ETL processes, and various datasets to generate actionable insights. The ETL (Extract, Transform, Load) pipeline is a critical part of this project.

It processes raw e-commerce data into clean, structured formats, ready for analysis. The ETL pipeline is implemented in Python within the ETL_ECommerce_Project.ipynb notebook. This ETL process is designed for flexibility and adaptability, making it a robust framework for handling e-commerce data workflows! This repository contains a comprehensive analysis of e-commerce sales data to uncover trends, customer behaviors, and product performance. The project demonstrates data cleaning, exploratory data analysis (EDA), and visualization techniques to derive actionable insights. This project is licensed under the MIT License.

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