Data Analysis Project Showcasing Customer Behavior 📊 Data Analytics Project – End-to-End Business Insights 📌 Overview
This project demonstrates an end-to-end data analytics workflow, covering data ingestion, exploratory data analysis (EDA), data cleaning, SQL-based analysis, interactive dashboarding, and business reporting.
The objective of this project is to extract meaningful insights from raw data and present them in a clear, decision-friendly format using industry tools such as Python, SQL, and Power BI.
📂 Dataset
Source: Customer shopping behavior dataset
Format: CSV
Key Attributes:
Customer demographics (Age, Gender, Location)
Product details (Category, Item Purchased)
Purchase metrics (Purchase Amount, Discounts, Subscription)
Ratings and seasonal information
🛠️ Tools & Technologies
Python: Pandas, NumPy, Matplotlib, Seaborn
SQL: PostgreSQL / MySQL / SQL Server
Database Connectivity: SQLAlchemy, psycopg2
Visualization: Power BI
Reporting: Power BI Report
Presentation: Gamma (PPT)
IDE: Jupyter Notebook
🔄 Project Workflow / Steps 1️⃣ Data Loading
Imported CSV dataset into Python using Pandas
Validated schema, data types, and missing values
2️⃣ Exploratory Data Analysis (EDA)
Univariate and multivariate analysis
Distribution analysis of numerical features
Category-wise and demographic-wise trends
Identification of outliers and inconsistencies
3️⃣ Data Cleaning & Preparation
Handled missing values
Standardized column names
Corrected data types
Removed duplicates and invalid records
4️⃣ SQL Analysis
Loaded cleaned data into relational databases
Executed analytical SQL queries such as:
Revenue by gender and age group
Top products by rating and sales
Subscriber vs non-subscriber spending
Discount impact on customer purchases
Used GROUP BY, CASE, JOIN, subqueries, and aggregations
5️⃣ Dashboard Development (Power BI)
Built an interactive dashboard including:
Revenue trends
Customer segmentation
Product performance
Subscription and discount insights
Added filters and slicers for dynamic analysis
6️⃣ Reporting & Presentation
Created a structured Power BI report
Designed a professional PPT using Gamma for stakeholder communication
Focused on insights, KPIs, and business recommendations
📊 Dashboard Highlights
Revenue contribution by gender and age group
Top-performing product categories
Impact of discounts on purchasing behavior
Subscriber vs non-subscriber comparison
Seasonal purchasing trends
📈 Key Results & Insights
Identified high-value customer segments
Found products with the highest revenue and ratings
Observed strong correlation between subscriptions and average spend
Highlighted age groups contributing the most to revenue
Provided actionable insights for marketing and sales strategies