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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
↓
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:
Author
Gourav Jangid
Aspiring Data Analyst
Open to Data Analytics Opportunities
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What if your online store could market itself? 🤖
I’ve been building an AI-powered social media automation platform that turns ecommerce products into ready-to-publish marketing content.
The workflow can:
→ Connect to an ecommerce store
→ Sync products automatically
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The bigger idea isn’t just “AI-generated posts.”
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This is the kind of automation I enjoy building: connecting APIs, AI agents, ecommerce systems, content generation, and social platforms into one practical workflow.
If you're running an ecommerce business and still creating every product post manually, there’s probably a lot that can be automated.
#AIAutomation #Ecommerce #AI #MarketingAutomation #SaaS #Automation #Contra
Love this autonomous workflow! Clean execution and super practical.
Data & Business Analyst | Turning raw data into decisions
Hi, I'm Ariful — a Data/Business Analyst with hands-on experience in supply chain operations and a growing skill set in Machine Learning, Deep Learning, and BI.
I work with Python, SQL, Power BI, and Excel to turn messy operational and financial data into predictive models and clear, actionable dashboards. Currently expanding into Generative AI (LangChain, HuggingFace).
Open to freelance work in data analysis, business analytics, and supply chain analytics.
Portfolio: https://ariful579.github.io
Retail Pulse is a comprehensive, 12-page interactive business intelligence solution built from scratch in Power BI. Designed to analyze a robust dataset of over 100,000 retail transaction records, this project transforms raw operational data into actionable strategic insights for executive decision-making.
The dashboards maintain a strict, professional visual hierarchy—utilizing a dark-themed canvas, strict conditional color logic (Green for Revenue, Blue for Profit), and dynamic cross-filtering to allow users to isolate performance by region, time, product, and customer cohort.
🛠️ Tech Stack & Tools
Data Visualization & BI: Power BI
Data Transformation: Power Query
Calculations & Measures: DAX (Data Analysis Expressions)
Complementary Skills: Python, SQL (Data Extraction & Validation)
📈 Key Dashboards & Features
Executive Summary: High-level overview of total business health (₹2.51B Total Revenue, 100K Total Customers).
Sales & Trend Analysis: Multi-year revenue growth tracking and seasonal peak identification.
Product Performance: Profitability mapping to isolate core revenue-driving inventory (e.g., Beds & Refrigerators).
Customer Analytics: High-value segmentation and geographic performance mapping across India.
Inventory Risk: Supply chain vulnerability tracking to identify high flight-risk stockouts.
Master Interactive Filter: A dedicated control panel allowing global cross-filtering across all 12 pages via Sync Slicers.
💡 Business Insights Generated
Customer Retention: Identified a 100% repeat customer rate, alongside a strict 90-day churn risk threshold.
Profit Efficiency: While May generates the highest gross volume, July yields the highest net profit margin due to optimized product mixes.
Regional Equality: Proven market penetration with revenue split almost evenly across Tier 1, Tier 2, and Village demographics.
