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DA - Data Warehousing

4 Chapters 21 Video Lectures Notes + PYQs PDF
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Ch. 1 Ch. 2 Ch. 3 Ch. 4
L1 - Introduction to Data Warehousing & Attribute Types
L2 - Statistical Description of Data
L3 - Problem Solving on Attribute Types & Statistical Description
L4 - Data Cleaning: Missing Values, Noise & Outliers
L5 - Data Reduction: PCA, Attribute Subset & Decision Trees
L6 - Data Reduction: Numerosity Reduction & Sampling
L7 - Data Compression: Lossless & Lossy Compression
L8 - Data Transformation & Normalization Techniques
L9 - Data Discretization & Binning Techniques
L10 - Data Discretization using Histogram Analysis
L11 - Problem Solving on Data Preprocessing
L12 - OLTP vs OLAP & Data Warehouse Architecture
L13 - Data Cubes & Types of Cuboids
L14 - Star, Snowflake & Fact Constellation Schemas
L15 - Concept Hierarchy & Levels of Abstraction
L16 - Categorization & Computation of Measures
L17 - OLAP Operations: Roll-Up, Drill-Down, Slice, Dice & Pivot
L18 - Problem Solving on Data Warehousing
Solutions to Problems 1–32 (Lecture 3)
Solutions to Problems 33–106 (Lecture 11)
Solutions to Problems 107–189 (Lecture 18)