Project

A course project proves you can build a working pipeline, from raw sources to a warehouse and actionable mining insights, not just understand theory. It becomes a portfolio asset that demonstrates practical impact: clean data, fast queries, and meaningful predictions/patterns.

Getting Started

List of Probable Project Topics

  • Retail Sales Data Warehouse + BI (star schema, ETL, OLAP queries, KPI dashboard)
  • Customer Segmentation Pipeline (warehouse + clustering + segment profiling)
  • Churn Prediction System (feature store/warehouse + ML model + monitoring metrics)
  • Market Basket Analysis (association rules + recommendations + drill-down reports)
  • Fraud/Anomaly Detection (transaction warehouse + anomaly mining + alerts)
  • Clickstream/Web Analytics Warehouse (sessionization + funnels + cohort analysis)
  • Healthcare Claims / EHR-style Warehouse (de-identified/public) (coding dimensions + risk patterns)
  • Supply Chain Warehouse (inventory, lead time, demand forecasting features)
  • Data Lake → Warehouse Migration (raw zone → curated zone → dimensional model)
  • Real-time ETL with Streaming Data (Kafka-like simulation + incremental loads)
  • Sentiment + Sales Fusion Warehouse (social text mining + sales correlation)
  • Credit Risk Mining (warehouse + scoring model + explainable features)
  • University/Student Analytics Warehouse (enrollment, grades, engagement; OLAP cubes)
  • Air Quality / Climate Warehouse (time-series warehouse + pattern mining + anomalies)
  • Product Recommendation Engine (warehouse features + collaborative filtering)
  • Data Quality & Lineage Framework (validation rules, audits, metadata tables)
  • SCD (Slowly Changing Dimensions) Implementation (Type 1/2 with history tracking)
  • SQL Performance & Indexing Study (query tuning + partitioning + benchmarks)