Certified Data Mining and Warehousing Professional

Data Warehousing Introduction

• Introduction
• Meaning of Data Warehousing
• History of Data Warehousing

Data Warehousing CharacterIstics

• Introduction
• Data Warehousing
• Operational vs. Informational Systems
• Characteristics of Data Warehousing

Online Transaction Processing

• Introduction
• Data Warehousing and OLTP Systems
• Processes in Data Warehousing OLTP
• What is OLAP?
• Who uses OLAP and WHY?
• Multi-Dimensional View s
• Benefits of OLAP

Data warehousing Models

• Introduction
• The Data Warehouse Model
• Data Modeling for Data Warehouses

Data warehousing Architecture

• Introduction
• Structure of a Data Warehouse
• Data Warehouse Physical Architectures
• Principles of a Data Warehousing

Data Warehousing And Operational Systems

• Introduction
• Operational Systems
• “ Warehousing” Data outside the Operational System s
• Integrating Data from more than one Operational System
• Differences between Transaction and Analysis Processes
• Data is mostly Non-volatile
• Data saved for longer periods than in transaction systems
• Logical Transformation of Operational Data
• Structured Extensible Data Model
• Data Warehouse model aligns with the business structure
• Transformation of the Operational State Information
• De-normalization of Data
• Static Relationships in Historical Data
• Physical Transformation of Operational Data
• Operational terms transformed into uniform business terms

Data Warehousing Considerations

• Introduction
• Building a Data Warehouse
• Nine Decisions in the design of a Data Warehouse

Data Warehousing-Applications

• Introduction
• Data Warehouse Application

Roi And Design Considerations

• Introduction
• Need of a Data Warehouse
• Business Considerations: Return on Investment
• Organizational Issues
• Design Considerations
• Data content
• Metadata
• Data Distribution
• Tools
• Performance Considerations

Technical And Implementation Considerations

• Introduction
• Technical Considerations
• Hardware Platforms
• Balanced Approach
• Optimal hardware architecture for parallel queryscalability
• Data warehouse and DBMS Specialization
• Communications Infrastructure
• Implementation Considerations
• Access Tools

Data Warehousing Benefits

• Introduction
• Benefits of Data Warehousing
• Problems with Data Warehousing
• Criteria for a Data Warehouse

Project Management Process

• Introduction
• Project Management Process
• The Scope Statement
• Project Planning
• Project Scheduling
• Software Project Planning
• Critical Path Method
• Decision Making

Work Breakdown Structure

• Introduction
• Work Breakdow n Structure (WBS)
• How to build a WBS (a serving suggestion)
• To Create Work Breakdown Structure
• From WBS to Activity Plan
• Estimating Time

Project Estimtion And Risk

• Introduction
• Project Estimation
• Analyzing Probability & Risk

Managing Risk

• Introduction
• Risk Analysis
• Risk Management
• Risk Analysis Managing Risks: Internal & External
• Internal and External Risks
• Critical Path Analysis

Data Mining Concepts

• Introduction
• Data Mining
• Data Mining Background
• Inductive Learning
• Statistics
• Machine Learning

Data Mining And Kdd

• Introduction
• What is Data Mining?
• Data Mining: Definitions
• KDD vs. Data Mining
• Stages OF KDD
• Machine Learning vs. Data Mining
• Data Mining vs. DBMS
• Data Warehouse
• Statistical Analysis

Elements Of Data Mining

• Introduction
• Elements and uses of Data Mining
• Relationships & Patterns
• Data Mining Problems/Issues
• Goals of Data Mining and Know ledge Discovery

Data Information And Knowledge

• Data, Information and Knowledge
• What can Data Mining do?
• How does Data Mining Work?
• Data Mining in a Nutshell

Data Mining Models

• Data Mining
• Data Mining Models
• Discovery of Association Rules
• Discovery of Classification Rules

Data Mining Issues And Challenges

• Other Mining Problems
• Data mining Application Areas
• Data Mining Applications-Case Studies
• Housing Loan Prepayment Prediction
• Mortgage Loan Delinquency Prediction
• Crime Detection
• Store-Level Fruits Purchasing Prediction
• Other Application Area

Dm Nearest Nighbor And Clustering Techniques

• Types of Knowledge Discovered during Data Mining
• Comparing the Technologies
• Clustering And Nearest-Neighbor Prediction Technique

Decision Trees

• What is a Decision Tree?
• Decision Trees
• Where to use Decision Trees?
• Tree Construction Principle
• The Generic Algorithm
• Guillotine Cut
• Over Fit

Decision Trees - Advanced

• Best Split
• Decision Tree Construction Algorithms
• Cart
• ID3
• C4.5
• Chaid
• How the Decision Tree Works
• State of the Industry

Neural Networks

• Basics of Neural Networks
• Are neural networks easy to use?
• Business Scorecard
• Where to use Neural Networks
• Neural Networks for Clustering
• Neural Networks for Feature Extraction
• Applications Score Card
• The General Idea

Neural Networks - Advanced

• What is a Neural Network Pparadigm?
• Design decisions in architecting a neural network
• Different types of Neural Networks
• Kohonen feature Maps
• Applications of Neural Networks
• Knowledge Extraction Through Data Mining

Association Rules And Genetic Algorithm

• Association Rules
• Basic Algorithms for Finding Association Rules
• Association Rules among Hierarchies
• Negative Associations
• Additional Considerations for Association Rules
• Genetic Algorithm
• Crossover
• Genetic Algorithms In detail
• Mutation
• Problem-Dependent Parameters
• Encoding
• The Evaluation Step
• Data Mining using GA

Olap Multidimensional Data Model

• On Line Analytical Processing
• OLAP Example
• What is OLAP?
• Who uses OLAP and WHY?
• Multi-Dimensional Views
• Complex Calculations
• Time Intelligence

Olap Characteristics

• Definitions of OLAP
• Characteristics of OLAP: FASMI
• Basic Features of OLAP
• Special features

Multidimensional And multirelational Olap

• Introduction
• Multidimensional Data Model
• Multidimensional versus Multi-relational OLAP
• OLAP Guidelines

Olap Operations

• Introduction OLAP Operations
• Lattice of Cubes, Slice and Dice Operations
• Relational Representation of the Data Cube
• DBMS

Data Mining

• Mining Association Rules
• Classification by Decision Trees and Rules
• Prediction Methods

Molap / Rolap Tools

• Categorization of OLAP Tools
• MOLAP
• ROLAP
• Managed Query Environment (MQE)
• Cognos PowerPlay