Columbia University’s M.S. in Applied Analytics is built for professionals looking to drive business strategy using data. These project ideas include visualization, operations optimization, KPI management, and business forecasting—designed to solve industry problems using practical analytics tools.
Predictive Analytics for E-Commerce Inventory Optimization
Customer Segmentation Using K-Means and RFM Analysis
Real-Time Sales Dashboard for Retail Chain Using Power BI
Churn Prediction Model for Subscription-Based Services
Social Media Sentiment Analytics for Brand Reputation
Forecasting Hotel Bookings Using Time Series Models
Campaign Performance Dashboard with A/B Testing Integration
Employee Attrition Predictor Using Logistic Regression
Customer Journey Mapping Using Google Analytics + BigQuery
Fraud Detection in Transaction Data Using Isolation Forest
Lead Scoring Model for B2B Sales Strategy
Operations Analytics Dashboard for Manufacturing KPIs
Predicting Credit Card Default Using XGBoost
Storytelling Dashboard for COVID-19 Vaccination Trends
Dynamic Pricing Engine for Ride-Sharing Apps Using Regression
Data Pipeline for Real-Time Stock Market Analysis
Recommendation Engine for Online Course Platforms
Web Traffic Forecasting for High-Traffic E-commerce Sites
Attrition Risk Heatmap for Human Resource Planning
Supply Chain Visualization and KPI Scorecard Integration
Collexa helps applied analytics students build dashboards, deploy models, clean datasets, and generate actionable insights using tools like Tableau, Power BI, Python, and SQL.
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