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Mastering Data Warehouse Design Relational and Dimensional Techniques

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ISBN-10: 0471324213

ISBN-13: 9780471324218

Edition: 2003

Authors: Claudia Imhoff, Nicholas Galemmo, Jonathan G. Geiger

List price: $45.00
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Description:

A cutting-edge response to Ralph Kimball's challenge to the data warehouse community that answers some tough questions about the effectiveness of the relational approach to data warehousing Written by one of the best-known exponents of the Bill Inmon approach to data warehousing Addresses head-on the tough issues raised by Kimball and explains how to choose the best modeling technique for solving common data warehouse design problems Weighs the pros and cons of relational vs. dimensional modeling techniques Focuses on tough modeling problems, including creating and maintaining keys and modeling calendars, hierarchies, transactions, and data quality
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Book details

List price: $45.00
Copyright year: 2003
Publisher: John Wiley & Sons, Incorporated
Publication date: 8/8/2003
Binding: Paperback
Pages: 456
Size: 7.25" wide x 9.00" long x 1.00" tall
Weight: 1.496
Language: English

Acknowledgments
About the Authors
Concepts
Introduction
Overview of Business Intelligence
BI Architecture
What Is a Data Warehouse?
Role and Purpose of the Data Warehouse
The Corporate Information Factory
The Multipurpose Nature of the Data Warehouse
Types of Data Marts Supported
Types of BI Technologies Supported
Characteristics of a Maintainable Data Warehouse Environment
The Data Warehouse Data Model
Nonredundant
Stable
Consistent
Flexible in Terms of the Ultimate Data Usage
The Codd and Date Premise
Impact on Data Mart Creation
Summary
Fundamental Relational Concepts
Why Do You Need a Data Model?
Relational Data-Modeling Objects
Subject
Entity
Element or Attribute
Relationships
Types of Data Models
Subject Area Model
Business Data Model
System Model
Technology Model
Relational Data-Modeling Guidelines
Guidelines and Best Practices
Normalization
Normalization of the Relational Data Model
First Normal Form
Second Normal Form
Third Normal Form
Other Normalization Levels
Summary
Model Development
Understanding the Business Model
Business Scenario
Subject Area Model
Considerations for Specific Industries
Subject Area Model Development Process
Subject Area Model for Zenith Automobile Company
Business Data Model
Business Data Development Process
Summary
Developing the Model
Methodology
Select the Data of Interest
Add Time to the Key
Add Derived Data
Determine Granularity Level
Summarize Data
Merge Entities
Create Arrays
Segregate Data
Summary
Creating and Maintaining Keys
Business Scenario
Inconsistent Business Definition of Customer
Inconsistent System Definition of Customer
Inconsistent Customer Identifier among Systems
Inclusion of External Data
Customers Uniquely Identified Based on Role
Customer Hierarchy Not Depicted
Data Warehouse System Model
Inconsistent Business Definition of Customer
Inconsistent System Definition of Customer
Inconsistent Customer Identifier among Systems
Absorption of External Data
Customers Uniquely Identified Based on Role
Customer Hierarchy Not Depicted
Data Warehouse Technology Model
Key from the System of Record
Key from a Recognized Standard
Surrogate Key
Dimensional Data Mart Implications
Differences in a Dimensional Model
Maintaining Dimensional Conformance
Summary
Modeling the Calendar
Calendars in Business
Calendar Types
Other Fiscal Calendars
Calendar Elements
Calendar Time Span
Time and the Data Warehouse
The Nature of Time
Standardizing Time
Data Warehouse System Model
Date Keys
Case Study: Simple Fiscal Calendar
Analysis
A Simple Calendar Model
Case Study: A Location Specific Calendar
Analysis
The GOSH Calendar Model
Delivering the Calendar
Case Study: A Multilingual Calendar
Analysis
Storing Multiple Languages
Handling Different Date Presentation Formats
Delivering Multiple Languages
Case Study: Multiple Fiscal Calendars
Analysis
Expanding the Calendar
Case Study: Seasonal Calendars
Analysis
Seasonal Calendar Structures
Delivering Seasonal Data
Summary
Modeling Hierarchies
Hierarchies in Business
The Nature of Hierarchies
Hierarchy Depth
Hierarchy Parentage
Hierarchy Texture
History
Summary of Hierarchy Types
Case Study: Retail Sales Hierarchy
Analysis of the Hierarchy
Implementing the Hierarchies
Case Study: Sales and Capacity Planning
Analysis
The Product Hierarchy
The Customer Hierarchy
Case Study: Retail Purchasing
Analysis
Implementing the Business Model
Case Study: The Combination Pack
Analysis
Adding a Bill of Materials
Publishing the Data
Transforming Structures
Making a Recursive Tree
Flattening a Recursive Tree
Summary
Modeling Transactions
Business Transactions
Business Use of the Data Warehouse
Average Lines per Transaction
Business Rules Concerning Changes
Application Interfaces
Snapshot Interfaces
Delta Interfaces
Database Transaction Logs
Delivering Transaction Data
Case Study: Sales Order Snapshots
Transforming the Order
Complete Snapshot Capture
Change Snapshot Capture
Change Snapshot with Delta Capture
Load Processing
Case Study: Transaction Interface
Modeling the Transactions
Processing the Transactions
Summary
Data Warehouse Optimization
Optimizing the Development Process
Optimizing Design and Analysis
Optimizing Application Development
Optimizing the Database
Data Clustering
Table Partitioning
Enforcing Referential Integrity
Index-Organized Tables
Indexing Techniques
Conclusion
Optimizing the System Model
Vertical Partitioning
Denormalization
Subtype Clusters
Summary
Operation and Management
Accommodating Business Change
The Changing Data Warehouse
Reasons for Change
Controlling Change
Implementing Change
Modeling for Business Change
Assuming the Worst Case
Imposing Relationship Generalization
Using Surrogate Keys
Implementing Business Change
Integrating Subject Areas
Adding Subject Areas
Summary
Maintaining the Models
Governing Models and Their Evolution
Subject Area Model
Business Data Model
System Data Model
Technology Data Model
Synchronization Implications
Model Coordination
Subject Area and Business Data Models
Business and System Data Models
System and Technology Data Models
Managing Multiple Modelers
Roles and Responsibilities
Collision Management
Summary
Deploying the Relational Solution
Data Mart Chaos
Why Is It Bad?
Criteria for Being in-Architecture
Migrating from Data Mart Chaos
Conform the Dimensions
Create the Data Warehouse Data Model
Create the Data Warehouse
Build New Data Marts Only "In-Architecture"--Leave Old Marts Alone
Build the Architecture from One Data Mart
Choosing the Right Migration Path
Summary
Comparison of Data Warehouse Methodologies
The Multidimensional Architecture
The Corporate Information Factory Architecture
Comparison of the CIF and MD Architectures
Scope
Perspective
Data Flow
Volatility
Flexibility
Complexity
Functionality
Ongoing Maintenance
Summary
Glossary
Recommended Reading
Index