Customer Behavior Analysis Dashboard Built with Python, PostgreSQL & Power BI

Excited to share a data analytics project I recently worked on! 📊 Customer Shopping Behavior Analysis Tools: SQL | Python | Power BI In this project, I analyzed over 3,900 customer transactions using SQL, Python, and Power BI to uncover meaningful business insights and trends. Key contributions: • Performed data cleaning and feature engineering using Python (Pandas) • Designed and queried a PostgreSQL database using SQL • Built interactive dashboards in Power BI for data visualization Key insights: • Subscription customers spend 68% more and demonstrate higher loyalty • Female customers contribute slightly higher revenue • Express shipping users show higher average transaction values. This project enhanced my ability to translate raw data into actionable business insights. 🔗 Project Link: https://lnkd.in/gTmmXjbS #DataAnalytics #SQL #Python #PowerBI #BusinessIntelligence #DataDriven

🚀 End-to-End Customer Shopping Behavior Analysis 🎥 Watch how this interactive dashboard uncovers key customer insights in seconds I worked on a complete data analytics project using Python, SQL, and Power BI to transform raw data into meaningful business insights. 🔍 What I did: • Cleaned and transformed 3,900+ records using Python • Performed SQL analysis in PostgreSQL • Built an interactive Power BI dashboard 📊 Key Insights: • Male customers generate 2x more revenue • 80% of customers are loyal repeat buyers • High-value customers still use discounts • Young Adults contribute the highest revenue 💡 Business Impact: These insights can help businesses improve marketing strategies, optimize discounts, and focus on high-value customer segments. 📌 Tools Used: Python | PostgreSQL | Power BI 🔗 Full Project (Code + SQL + Dashboard): https://lnkd.in/gSmEVwng Would love your feedback! #DataAnalytics #SQL #PowerBI #Python #BusinessAnalytics #DataScience #AnalyticsProject Amlan Mohanty

🚀 Excited to share my Data Analytics Project: Customer Shopping Behavior Analysis I analyzed 3,900+ customer transactions to understand spending patterns, customer segments, and product trends. 🔧 Tools Used: Python (Pandas) | SQL | Power BI 📊 What I did: Cleaned and processed raw data using Python Performed SQL analysis to extract business insights Built an interactive Power BI dashboard 💡 Key Insights: Young adults contribute the highest revenue Loyal customers form the largest segment Non-subscribers drive the majority of total sales #DataAnalytics #Python #SQL #PowerBI #DataScience

🚀 Customer Behavior Analysis Dashboard Built a data analytics project to understand customer shopping patterns using ~3,900 transactions. 🔍 What I did: Cleaned & transformed raw data using Python (Pandas) Performed EDA to uncover patterns Ran SQL queries (PostgreSQL) for business analysis Built an interactive Power BI dashboard Created a detailed report and presentation 📊 Key insights: Segmented customers into loyal, returning, and new Identified high-revenue age groups Analyzed impact of discounts and subscriptions Found top-performing products and categories 💡 Takeaway: Data only matters when it answers real business questions. This project focuses on turning raw data into actionable insights. 🔗 Project Link: https://lnkd.in/gD4gn3Xq #data_analysis #PowerBi #SQL #Python #Data_insights

🚀 Excited to share my latest Data Analytics Project! 📊 Customer Behavior Analysis using Python, SQL & Power BI In this project, I analyzed customer purchasing behavior to uncover actionable insights and trends. 🔍 Key Highlights: • Data cleaning and preprocessing using Python • Performed Exploratory Data Analysis (EDA) • Used SQL for querying and insights extraction • Built an interactive Power BI dashboard 📈 Key Insights: • High-value customers contribute most of the revenue • Certain product categories perform better • Seasonal trends impact purchasing behavior • Discounts influence buying frequency 📊 The dashboard helps businesses make data-driven decisions and understand customer trends. 🔗 GitHub Repository: (https://lnkd.in/g9UZmNs8) #DataAnalytics #Python #SQL #PowerBI #DataScience #Portfolio #Projects

I recently worked on a Customer Behavior Dashboard to analyze sales performance, customer trends, and product insights. Tools Used: Excel | Python | SQL | Power BI Key Insights: • A few top product categories contribute to the majority of overall revenue • Customers purchasing discounted items showed higher buying frequency • Certain categories generated high sales but lower profit margins • Revenue trends highlighted peak purchasing periods and seasonal demand What I Did: • Cleaned and transformed raw data using Python & SQL • Built Pivot Tables & Charts in Excel for initial analysis • Created KPIs like Total Sales, Revenue, and Category Performance • Designed an interactive Power BI dashboard with slicers for dynamic filtering • Visualized customer behavior and top-performing products. What I Learned: • End-to-end data analysis workflow (cleaning → analysis → visualization) • How to extract meaningful business insights from raw datasets • Building interactive dashboards for decision-making 📷 Dashboard preview attached below 🔗 GitHub: https://lnkd.in/g7VN3GeS #DataAnalytics #PowerBI #SQL #Python #Excel #DataAnalyst #PortfolioProject

In today’s business world, understanding customer behavior patterns is crucial to staying competitive and relevant. Just completed a project analyzing customer shopping behavior using Python (Pandas) and SQL, then connected the data into Power BI to build an interactive dashboard for clear, visual insights. 💡 Adding meaningful projects and applying skills not only strengthens a CV but also builds confidence. Key Outcome: Identified purchase drivers and subscription patterns, helping guide smarter, data‑driven business decisions. Link: https://lnkd.in/demMNXTy #sql #python #postgreSQl #powerbi #dax #datanalytics

📊 End-to-End Data Analytics Project Completed! Excited to share my latest project on Customer Behavior Analysis, where I worked on a complete data analytics pipeline from raw data to meaningful insights 🔹 Data loading & preprocessing using Python 🔹 Data cleaning and Exploratory Data Analysis (EDA) 🔹 SQL analysis using PostgreSQL Server 🔹 Built an interactive dashboard using Power BI 🔹 Created a detailed report and presentation using Gamma 🔗 GitHub Repository: https://lnkd.in/grukmeSd This project helped me strengthen my skills in data analysis, SQL, and data visualization, and understand how data-driven insights can support better decision-making. Projects like these reflect how real-world datasets can be transformed into actionable business insights 📈 Looking forward to building more impactful projects and growing in the field of data analytics. #DataAnalytics #Python #SQL #PowerBI #EDA #DataScience #LearningJourney #AI #StudentProjects #GitHub

I didn’t want my first Data Analysis project to be just another tutorial copy. So I built everything from scratch. I created an entire e-commerce dataset (Shreeji Collection) — from structuring tables to generating 6.7K+ rows of transactional data — just to understand how real business data actually behaves. Then I worked on it like a real analyst: • Used SQL to break down revenue trends and customer behavior • Cleaned raw, inconsistent data using Python (Pandas, NumPy) • Transformed analysis into interactive dashboards using Power BI What stood out to me wasn’t the tools — it was how small patterns in data can explain real business decisions. This project changed how I look at data. Not as numbers — but as signals. Still learning. Still building. 🚀 #DataAnalytics #SQL #Python #PowerBI #Projects

Just completed my Customer Behavior Analysis Project! I analyzed 3,900+ customer transactions to understand how customers interact with products, subscriptions, and discounts — and how businesses can use this data to make better decisions. Tech Stack: • Python (Jupyter Notebook) – Data Cleaning & Feature Engineering • SQL (PostgreSQL) – Business Analysis • Power BI – Interactive Dashboard Key Findings: • Only ~27% customers are subscribed → huge growth opportunity • Loyal customers show the highest conversion to subscriptions • Clothing category generates the highest sales • Discounts positively influence customer engagement • Sales remain stable across seasons What makes this project valuable: Instead of just building visuals, I focused on extracting actionable insights that can help businesses improve customer retention, optimize marketing strategies, and increase revenue. GitHub Repository: https://lnkd.in/gJUR_kuz Would love to hear your feedback #DataAnalytics #PowerBI #SQL #Python #DataAnalysis #AnalyticsProject #LearningInPublic