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Introduction to Data Mining & Data Warehousing

[Hook/Intro] Welcome to this comprehensive guide on Data Warehousing! In this video, we break down the core concepts of Data Mining and Data Warehousing, covering everything from basic definitions to complex schema designs. Whether you are a student or a data enthusiast, this overview will help you master the fundamentals. [Timestamps / Key Topics Covered] • Introduction to Data Warehouse: Understanding the definition and key characteristics (Subject-Oriented, Integrated, Time-Variant, Non-Volatile). • OLTP vs. Data Warehouse: The critical differences between operational systems and analytical processing. • Architecture: A look at Single-tier, Two-tier, and the industry-standard Three-tier architectures. • Core Components: Explaining ETL (Extract, Transform, Load), Metadata, and Data Marts. • Schema Design: Deep dive into Star, Snowflake, and Fact Constellation schemas. • Data Modeling: Understanding Fact Tables (Transaction, Snapshot, Accumulated) and Measures (Additive, Semi-Additive). • OLAP Operations: How OLAP Cubes work, including Roll-up, Drill-down, Slice, Dice, and Pivot operations. • Types of OLAP: A comparison of ROLAP, MOLAP, and HOLAP systems. Powered by NotebookLM This content was researched, summarized, and structured with the assistance of NotebookLM by Google, an AI research assistant that grounded the information directly in the provided study materials.