Building the Data Warehouse

Building the Data Warehouse

by William H. Inmon
     
 

ISBN-10: 0894354043

ISBN-13: 9780894354045

Pub. Date: 01/15/1992

Publisher: Wiley

Since it was first published in 1990, W. H. Inmon's Building the Data Warehouse has become the bible of data warehousing -- the first and best introduction to the subject. A lot has changed in data warehousing technology since the last edition appeared in 1996, and this latest volume is completely revised to reflect exciting new techniques and applications, update

Overview

Since it was first published in 1990, W. H. Inmon's Building the Data Warehouse has become the bible of data warehousing -- the first and best introduction to the subject. A lot has changed in data warehousing technology since the last edition appeared in 1996, and this latest volume is completely revised to reflect exciting new techniques and applications, update existing topics, and examine data marts, operational data stores, and the corporate information factory. In this Third Edition, Inmon explains what a data warehouse is (and isn't), why it's needed, how it works, and how the traditional data warehouse can be integrated with new technologies, including the Web, to provide enhanced customer service and support. He also addresses the trade-offs between normalized data warehouses and dimensional data marts.

Product Details

ISBN-13:
9780894354045
Publisher:
Wiley
Publication date:
01/15/1992
Pages:
272

Table of Contents

Preface for the Second Editionxiii
Preface for the Third Editionxiv
Acknowledgmentsxix
About the Authorxx
Chapter 1Evolution of Decision Support Systems1
The Evolution2
The Advent of DASD4
PC/4GL Technology4
Enter the Extract Program5
The Spider Web6
Problems with the Naturally Evolving Architecture6
Lack of Data Credibility6
Problems with Productivity9
From Data to Information12
A Change in Approach15
The Architected Environment16
Data Integration in the Architected Environment19
Who Is the User?19
The Development Life Cycle21
Patterns of Hardware Utilization22
Setting the Stage for Reengineering23
Monitoring the Data Warehouse Environment25
Summary28
Chapter 2The Data Warehouse Environment31
The Structure of the Data Warehouse35
Subject Orientation36
Day 1-Day n Phenomenon41
Granularity43
The Benefits of Granularity45
An Example of Granularity46
Dual Levels of Granularity49
Exploration and Data Mining53
Living Sample Database53
Partitioning as a Design Approach55
Partitioning of Data56
Structuring Data in the Data Warehouse59
Data Warehouse: The Standards Manual64
Auditing and the Data Warehouse64
Cost Justification65
Justifying Your Data Warehouse66
Data Homogeneity/Heterogeneity69
Purging Warehouse Data72
Reporting and the Architected Environment73
The Operational Window of Opportunity74
Incorrect Data in the Data Warehouse76
Summary77
Chapter 3The Data Warehouse and Design81
Beginning with Operational Data82
Data/Process Models and the Architected Environment87
The Data Warehouse and Data Models89
The Data Warehouse Data Model92
The Midlevel Data Model94
The Physical Data Model98
The Data Model and Iterative Development102
Normalization/Denormalization102
Snapshots in the Data Warehouse110
Meta Data113
Managing Reference Tables in a Data Warehouse113
Cyclicity of Data-The Wrinkle of Time115
Complexity of Transformation and Integration118
Triggering the Data Warehouse Record122
Events122
Components of the Snapshot123
Some Examples123
Profile Records124
Managing Volume126
Creating Multiple Profile Records127
Going from the Data Warehouse to the Operational Environment128
Direct Access of Data Warehouse Data129
Indirect Access of Data Warehouse Data130
An Airline Commission Calculation System130
A Retail Personalization System132
Credit Scoring133
Indirect Use of Data Warehouse Data136
Star Joins137
Supporting the ODS143
Summary145
Chapter 4Granularity in the Data Warehouse147
Raw Estimates148
Input to the Planning Process149
Data in Overflow?149
Overflow Storage151
What the Levels of Granularity Will Be155
Some Feedback Loop Techniques156
Levels of Granularity-Banking Environment158
Summary165
Chapter 5The Data Warehouse and Technology167
Managing Large Amounts of Data167
Managing Multiple Media169
Index/Monitor Data169
Interfaces to Many Technologies170
Programmer/Designer Control of Data Placement171
Parallel Storage/Management of Data171
Meta Data Management171
Language Interface173
Efficient Loading of Data173
Efficient Index Utilization175
Compaction of Data175
Compound Keys176
Variable-Length Data176
Lock Management176
Index-Only Processing178
Fast Restore178
Other Technological Features178
DBMS Types and the Data Warehouse179
Changing DBMS Technology181
Multidimensional DBMS and the Data Warehouse182
Data Warehousing across Multiple Storage Media188
Meta Data in the Data Warehouse Environment189
Context and Content192
Three Types of Contextual Information193
Capturing and Managing Contextual Information194
Looking at the Past195
Refreshing the Data Warehouse195
Testing198
Summary198
Chapter 6The Distributed Data Warehouse201
Types of Distributed Data Warehouses202
Local and Global Data Warehouses202
The Technologically Distributed Data Warehouse220
The Independently Evolving Distributed Data Warehouse221
The Nature of the Development Efforts222
Completely Unrelated Warehouses224
Distributed Data Warehouse Development226
Coordinating Development across Distributed Locations227
The Corporate Data Model-Distributed228
Meta Data in the Distributed Warehouse232
Building the Warehouse on Multiple Levels232
Multiple Groups Building the Current Level of Detail235
Different Requirements at Different Levels238
Other Types of Detailed Data239
Meta Data244
Multiple Platforms for Common Detail Data244
Summary245
Chapter 7Executive Information Systems and the Data Warehouse247
EIS-The Promise248
A Simple Example248
Drill-Down Analysis251
Supporting the Drill-Down Process253
The Data Warehouse as a Basis for EIS254
Where to Turn256
Event Mapping258
Detailed Data and EIS261
Keeping Only Summary Data in the EIS262
Summary263
Chapter 8External/Unstructured Data and the Data Warehouse265
External/Unstructured Data in the Data Warehouse268
Meta Data and External Data269
Storing External/Unstructured Data271
Different Components of External/Unstructured Data272
Modeling and External/Unstructured Data273
Secondary Reports274
Archiving External Data275
Comparing Internal Data to External Data275
Summary276
Chapter 9Migration to the Architected Environment277
A Migration Plan278
The Feedback Loop286
Strategic Considerations287
Methodology and Migration289
A Data-Driven Development Methodology291
Data-Driven Methodology293
System Development Life Cycles294
A Philosophical Observation294
Operational Development/DSS Development294
Summary295
Chapter 10The Data Warehouse and the Web297
Supporting the Ebusiness Environment307
Moving Data from the Web to the Data Warehouse307
Moving Data from the Data Warehouse to the Web308
Web Support309
Summary310
Chapter 11ERP and the Data Warehouse311
ERP Applications Outside the Data Warehouse312
Building the Data Warehouse inside the ERP Environment314
Feeding the Data Warehouse through ERP and Non-ERP Systems314
The ERP-Oriented Corporate Data Warehouse318
Summary320
Chapter 12Data Warehouse Design Review Checklist321
When to Do Design Review322
Who Should Be in the Design Review?323
What Should the Agenda Be?323
The Results323
Administering the Review324
A Typical Data Warehouse Design Review324
Summary342
Appendix343
Glossary385
Reference397
Index407

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