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Performed end-to-end data analysis using Python, including data cleaning, preprocessing, exploratory data analysis, visualization, machine learning, clustering, regression, time-series analysis, and NLP sentiment analysis. Built and evaluated customer churn classification models using Scikit-learn, including Random Forest, Decision Tree, and Logistic Regression, with hyperparameter tuning using GridSearchCV.
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AI-Assisted Sales Intelligence Dashboard
Project Overview
This project is an end-to-end Sales Analytics solution built using Python, SQL, and Power BI.
The workflow includes:
Data Cleaning using Python (Pandas)
Data Storage using SQLite
Business Analysis using SQL Queries
Interactive Dashboard using Power BI
Automated Business Report Generation using Python
The goal of this project is to analyze sales performance, identify profitable products, monitor regional performance, and generate business recommendations.
Dataset
Dataset: Sample Superstore Dataset
Records: 9,994
Features:
Order Details
Customer Information
Product Information
Sales
Profit
Discount
Region
Category
Sub-Category
Tools & Technologies
Python
Pandas
SQLite
SQL
Power BI
Data Visualization
Business Intelligence
Project Workflow
CSV Dataset
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Data Cleaning (Python)
↓
SQLite Database
↓
SQL Analysis
↓
Power BI Dashboard
↓
AI Business Report
Dashboard Pages
Executive Overview Total Sales Total Profit Total Orders Profit Margin Regional Sales Analysis Category Performance Analysis
Product Performance Analysis Top Profitable Products Loss-Making Products Profit by Category Sales by Sub-Category
Sales Trends Analysis Sales Trends Over Time Profit Trends Seasonal Performance Insights Key Business Insights West Region generated the highest sales. Technology is the most profitable category. Several products generate significant losses and require pricing review. Sales performance varies significantly across regions. Automated AI Report The project includes a Python-based reporting system that automatically generates:
Total Sales
Total Profit
Business Insights
Strategic Recommendations
Author
Gourav Jangid
Aspiring Data Analyst
Open to Data Analytics Opportunities
Created an AI-powered lead generation and outreach tool for finding and converting local business leads.
The system scrapes Google Maps, analyzes business websites with Gemini AI, and generates personalized pitch emails automatically.
I built the complete pipeline from scraping to AI analysis and outreach.
Tech: Node.js, Puppeteer, Gemini AI, Express, Next.js
🎥 Project demo: Reel attached below.
good job
Manufacturing ERP & Production Intelligence Dashboard
The dark plant nav next to the light data canvas keeps the menus from fighting the charts. Putting the packing trend beside stock balance makes the floor numbers readable at a glance.