Building A Better Data Warehouse

Building A Better Data Warehouse

by Don Meyer

Hardcover

$41.99

Product Details

ISBN-13: 9780138907570
Publisher: Prentice Hall Professional Technical Reference
Publication date: 12/24/1997
Pages: 256
Product dimensions: 7.23(w) x 9.55(h) x 0.94(d)

Table of Contents

Preface ix(6)
Foreword xv(2)
Acknowledgments xvii(2)
Trademarks xix
Section 1 Introducing the Data Warehouse 1(38)
Chapter 1 Reality and the Vision: Executive Overview
3(16)
Understanding the Role of the Data Warehouse
6(2)
Determining Your Return on Investment (ROI)
8(2)
Leveraging the Internet
10(1)
Building the Data Warehouse
11(4)
Critical Success Factors
15(4)
Chapter 2 Data Warehousing 101
19(20)
What is a Data Warehouse?
20(2)
OLAP versus OLTP Applications
22(2)
Multidimensional Data Storage
24(1)
Data Warehouse Architecture
25(4)
Data Warehouse Infrastructure
29(4)
Parallel Hardware
30(1)
Data Extraction, Transformation, and Scrubbing
31(1)
Data Storage
31(1)
Meta Data
32(1)
Data Access
32(1)
Data Delivery
32(1)
Understanding the Data Model
33(4)
The Pilot Project
37(2)
Section 2 Managing the Data Warehouse 39(78)
Chapter 3 It's Just Business: Data Warehouse Project Management
41(28)
Assembling the Initial Team
43(3)
Readiness Assessment
46(1)
Determining the Initial Business Requirements
47(1)
Organizing the Project Plan and Scope
48(6)
Project Scope Document
49(1)
Scope
49(2)
Infrastructure
51(1)
Management
52(2)
Building the Project Plan
54(7)
Assembling the Support Team
61(2)
Assembling Additional Business Requirements
63(4)
What Am I Trying to Find Out?
65(2)
By the Way
67(2)
Chapter 4 Choose Your Weapons
69(48)
Which Way to Go?
73(10)
Data Warehouse or Data Mart?
73(2)
Understanding Data Marts
75(1)
What If?
76(2)
MOLAP or ROLAP?
78(3)
Multiple Vendors or Single Solution Provider?
81(2)
Identifying the Pieces of the Puzzle
83(34)
Database Storage
83(13)
End-user Tools
96(3)
Hardware Platform
99(4)
Storage Subsystems
103(3)
Extraction, Transformation, and Scrubbing Tools
106(3)
Meta Data Tools
109(3)
Data Modeling / CASE Tools
112(5)
Section 3 Building the Data Warehouse 117(92)
Chapter 5: Understand the Data: Data Modeling
119(20)
Building the Data Model
121(7)
Level 1
124(2)
Level 2
126(1)
Level 3
127(1)
Modeling Effort Scope
128(1)
Identifying Data Sources
129(3)
Building the Dimensional Model
132(7)
Chapter 6 Datamagic: Database Administration
139(20)
Capacity Planning
141(5)
Disk Storage Capacity
142(3)
Processor Capacity
145(1)
Database Administration
146(6)
Performance Tuning
147(4)
Security
151(1)
Creating and Loading the Data Warehouse
151(1)
Designing and Building the Physical Model
152(7)
Chapter 7 _?_ Changes Everything: a. Extraction b. Transformation c. Scrubbing
159(10)
Extraction, Transformation, & Scrubbing Tools
161(1)
Data Loading
162(7)
Post-load Processes
164(1)
Program Function Specification and Data Flow Diagram Examples
165(4)
Chapter 8 Digging for Data: Meta Data
169(10)
Using Meta Data for Mapping Data
172(2)
Meta Data Management
174(2)
Navigating the Meta Data
176(3)
Chapter 9 Show Me the Data: End-user Access
179(14)
End-user Tool Architecture
181(4)
Data Mining
185(4)
Data Mining Tools
187(2)
Leveraging the Internet
189(4)
Chapter 10 Under Construction: Construction, Testing and Rollout
193(12)
Construction, Testing and Rollout Checklist
195(4)
Data Quality
199(1)
Documentation (Process Maintenance Development)
199(1)
Change Control
200(1)
Testing
201(1)
Rollout and Training
202(1)
Post-implementation Review
203(2)
Chapter 11 In Conclusion
205(4)
Terms and Technologies 209(6)
Acronyms 215(2)
Index 217

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