E Commerce Sales Analysis Readme Md At Main Github

There was an error while loading. Please reload this page. A comprehensive data analysis report examining 1,000 products across 7 categories with 12 months of sales data. The objective of this report is to identify the strengths, weaknesses, opportunities, and threats (risks) of the e-commerce business. Using these insights, I will provide clear, actionable recommendations to support strategic decision-making and business growth. Public Dataset available on [https://www.kaggle.com/datasets/fahmidachowdhury/e-commerce-sales-analysis]

The market shows surprising balance with the top 3 categories (Books, Toys, Sports) commanding 46% of total sales. Critical Discovery: Price has virtually NO correlation with sales performance There was an error while loading. Please reload this page. There was an error while loading. Please reload this page.

Comprehensive retail analytics demonstrating marketing efficiency measurement, customer segmentation, and performance optimization This project analyzes a full e-commerce retail dataset to uncover opportunities in marketing efficiency, customer value, regional performance, and revenue optimization. It mirrors the analytical responsibilities of a Commerce Insights & Analytics role, with a strong focus on ROAS measurement, customer segmentation, A/B testing, and actionable insights. This analysis evaluates key retail performance drivers across: The goal is to illustrate how data can inform marketing allocation, campaign design, and customer growth strategy. The project simulates real-world expectations for a Commerce Insights & Analytics team:

There was an error while loading. Please reload this page. Data analysis is considered the backbone of every ecommerce business. In this project, we import, clean, and analyze the dataset from an e-commerce store. For that purpose, we use SQL for queries, Pandas for data manipulation and visualization libraries to extract insights. The main purpose of this project is to create key insights such as revenue trend, top products, customer behavior, and regional performance.

This project is divided into five main parts. Objective: Store the dataset in an SQLite database. In the first task, we create a database and populate it with tables using the provided CSV files. Here, read_csv() function is used to load the data, and the to_sql() function converts it into database tables. 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.

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