Data Warehousing & Data Mining : Express Learning

Cover
Contents
Preface
Chapter 1: Introduction to Data Warehouse
	For Using the Data Warehouse
	For Building the Data Warehouse
	For Administering the Data Warehouse
	Business Metadata
	Technical Metadata
	Reporting and Managed Query Tools
	OLAP Tools
	Application Development Tools
	Data Mining Tools
	Data Visualization Tools
	First Generation Client/Server Model
	Second Generation Client/Server Model
	Multiple Choice Questions
	Answers
Chapter 2: Building a Data Warehouse
	Business Considerations
	Design Considerations
	Technical Considerations
	Implementation Considerations
	Data Partitioning
	Data Clustering
	Parallel Processing
	Summary Levels
	Multiple Choice Questions
	Answers
Chapter 3: Data Warehouse: Architecture
	Compute Cube Operator
	Partial Materialization
	Star Schema
	Snowflake Schema
	Fact Constellation Schema
	Multiple Choice Questions
	Answers
Chapter 4: OLAP Technology
	MOLAP Architecture
	Data Design and Preparation
	Administration
	Performance
	OLAP Platforms
	OLAP Tools and Products
	Implementation Steps
	Indexing OLAP Data
	Processing of OLAP queries
	Multiple Choice Questions
	Answers
Chapter 5: Introduction to Data Mining
	Class/Concept Description
	Mining Frequent Patterns, Associations and Correlations
	Classification and Prediction
	Cluster Analysis
	Outlier Analysis
	Evolution Analysis
	On the Basis of Prediction/Description
	On the Basis of Automatic/Manual Mining of Data
	Multiple Choice Questions
	Answers
Chapter 6: Data Preprocessing
	Wavelet Transforms
	Principal Components Analysis (PCA)
	Regression
	Log-Linear Models
	Histograms
	Clustering
	Sampling
	Input
	Output
	Procedure
	Explanation
	Multiple Choice Questions
	Answers
Chapter 7: Mining Association Rules
	Generalized Association Rules
	Multi-level Association Rules
	Multidimensional Association Rules
	Multiple Choice Questions
	Answers
Chapter 8: Classification and Prediction
	Naive Bayesian
	Bayesian Belief Network
	Linear Regression
	Non-linear Regression
	Bagging
	Boosting
	Multiple Choice Questions
	Answers
Chapter 9: Cluster Analysis
	Statistical Distribution-based Outlier Detection
	Distance-based Outlier Detection
	Density-based Local Outlier Detection
	Deviation-based Outlier Detection
	Multiple Choice Questions
	Answers
Chapter 10: Advanced Techniques of Data Mining and Its Applications
	Financial Data Analysis
	Retail Industry
	Intrusion Detection
	Telecommunication Industry
	Multiple Choice Questions
	Answers
Index