Developing Analytical Database Applications

Developing Analytical Database Applications

by Francis McGuff, John Kador

Paperback

$57.00

Product Details

ISBN-13: 9780130824301
Publisher: Prentice Hall Professional Technical Reference
Publication date: 12/22/1998
Pages: 640
Product dimensions: 7.04(w) x 9.25(h) x 1.78(d)

Table of Contents

Preface xix(2)
Acknowledgments xxi(1)
About the Authors xxii
Chapter 1 Knowledge Workers and Analytical Applications
1(30)
What Are Analytical Applications?
3(2)
The Business Need for Analytical Applications
5(2)
Downsized Organizations
5(1)
Brittle Systems
6(1)
Dispersed Decision Making
6(1)
Faster Access to Information
7(1)
Knowledge Workers and Analytical Applications
7(3)
What Knowledge Workers Require
8(1)
What Knowledge Workers Want
9(1)
The Structure of Methodologies
10(18)
Task Domain Analysis
12(7)
User Domain Analysis
19(6)
Data Domain Analysis
25(3)
Summary
28(3)
Chapter 2 A Model For Analytical Applications
31(38)
Typical Analytical Applications
31(8)
Sales Performance
32(2)
Budgeting and Planning
34(2)
Manufacturing
36(2)
Common Elements in Analytical Applications
38(1)
A Model of Analytical Applications
39(28)
Deep Structure
41(11)
The Surface Structure
52(12)
Life At the Interface
64(3)
Summary
67(2)
Chapter 3 Decision Support and Analytical Applications
69(30)
The Components of information
70(3)
Content
70(1)
Structure
71(1)
Delivery
72(1)
Knowledge Worker Tasks
73(6)
Monitoring & Reporting
73(1)
Analysis & Diagnosis
74(4)
Simulation & Planning
78(1)
DSS Technology Space
79(6)
Data Acquisition Quality and Delivery
80(1)
Query and Report Writers
81(1)
Managed Query Environment
82(2)
Data Visualization
84(1)
Data Mining
85(1)
Architectures for Analytical Applications
85(5)
Relational Online Analytical Processing (ROLAP)
86(1)
Multi-dimensional Databases (MDBs)
87(1)
Hybrid OLAP
88(1)
Which Technology is More Suitable?
89(1)
Technology Requirements in the DSS Space
90(7)
Summary
97(2)
Chapter 4 Dimensional Structure of Analytical Applications
99(34)
Multi-dimensional Views
100(5)
The Structure of Information
105(3)
Types of Dimensions
108(8)
Structural Dimensions
108(3)
Information Dimensions
111(1)
Partitioning Dimensions
112(2)
Categorical Dimensions
114(2)
More about Dimensions
116(8)
Multicubes vs. Hypercubes
118(1)
Dimension Depth and Height
119(1)
Data Sparsity
120(3)
Dimensional Explosion
123(1)
Dimensional Databases
124(8)
The Star Schema
125(6)
Deciding between MDBs and RDBs
131(1)
Summary
132(1)
Chapter 5 Architecture for Analytical Applications
133(46)
A Sample Database
134(4)
The Semantics of Information
138(4)
An Example of a Semantic Ambiguity
140(2)
Analytical Database Terms and Definitions
142(23)
Notes on Facts and Dimensions
144(7)
Implementing dimensional tables
151(14)
Requirements
165(12)
Monitoring and reporting
166(5)
Sharing results
171(1)
Analysis and diagnosis
172(3)
Simulation and planning
175(2)
Summary
177(2)
Chapter 6 A Methodology for Analytical Applications
179(48)
System Model and Documentation
181(1)
What is a Methodology?
182(13)
Different Kinds of Methodologies
184(11)
Summary of Four Quadrants
195(23)
Quadrant I: Vision & Scope
198(7)
Quadrant II: Design
250(6)
Quardant III: Build
211(4)
Quadrant IV: Development
215(3)
Project Planning
218(8)
Task Management
220(2)
Developing the Plan
222(4)
Summary
226(1)
Chapter 7 Vision & Scope
227(44)
Application Goals and Constraints
229(10)
Monthly Close Processing
232(1)
IS Staffing Level
232(1)
System Availability
233(1)
Data Center Operations
233(1)
Technology Decisions
234(1)
End-user Computing
234(1)
Setting Goal Priorities
235(4)
Vision & Scope: Purpose
239(1)
Vision & Scope: Deliverables
239(16)
Introduction
242(3)
Purpose
245(1)
Goals and Constraints
245(9)
Readiness Assessment
254(1)
Project Planning
255(1)
Glossary
255(1)
Vision & Scope Actions
255(15)
Schedule of Events for Vision & Scope
256(1)
The Consensus Meeting
257(8)
Collaborative Sessions
265(1)
Readiness Assessment
266(3)
Commitment Meeting
269(1)
Summary
270(1)
Chapter 8 Design
271(48)
Purpose
272(2)
Design Qualities
273(1)
Deliverables: Design Document
274(31)
Management Documentation
275(2)
Functional Documentation
277(1)
Participatory Design
277(16)
Technical Documentation
293(12)
Activities: Defining the Business Processes
305(11)
Collaborative Design Sessions
305(1)
Source System Analysis
305(1)
Analytical Process Analysis
306(2)
Actions
308(1)
Business Process Design
308(6)
Assessment
314(1)
Planning
315(1)
Commitment Meeting
316(1)
Summary
316(3)
Chapter 9 Build and Deployment
319(28)
Build
320(21)
Imperative #1: Ship Every Day
320(2)
Imperative #2: Can we Stop Today?
322(1)
The Project Plan
322(10)
For Each Build Deliverable
332(3)
Assessment
335(1)
Risk management and problem solving
336(4)
Planning
340(1)
Deployment
341(4)
Rollout #n
341(4)
Summary
345(2)
Chapter 10
347(72)
A Little Story
348(1)
The Whole from the Parts
349(1)
The Perfect Data Warehouse
350(3)
Semantics vs. Structure
353(2)
The Star Architecture
355(1)
Data Modeling
356(1)
Introduction
356(1)
The Steps
356(1)
The Business Model
357(4)
Data Model Analysis
357(2)
Model Normalization
359(1)
Integrity Constraints
360(1)
Dimensional Model
361(34)
Structural Dimensions
361(22)
Informational Dimensions
383(2)
Categorical Dimensions
385(3)
Partitioning Dimensions
388(2)
Slowly Changing Dimensions
390(5)
Physical Model
395(5)
General Objectives
395(5)
Categorical Dimensions
400(1)
Connectedness and Complexity
400(4)
Complexity
401(3)
Sample Data Warehouses
404(10)
The Retail Model
405(3)
Health Care Manufacturing
408(6)
Summary
414(1)
Stars, Snowflakes and Galaxies
414(4)
Summary
418(1)
Chapter 11
419(44)
Functional vs. Component Decomposition
420(4)
When to Stop
422(2)
Object Analysis
424(21)
Use Case Analysis
427(1)
Class Relationships
427(4)
The Process
431(14)
Summary
445(1)
The Analytical Application
445(17)
Step 1: The Use Case Scenario
446(6)
Step 2: Functional Decomposition
452(7)
Step 3: Definition of Input-Operator-Output
459(2)
Step 4: Normalization of Candidate Classes
461(1)
Step 5: Abstraction of the Class Structure
461(1)
Summary
462(1)
Chapter 12
463(52)
Dimension Class Model
465(7)
Hypercube Class Model
472(8)
Hypercube Representations
473(7)
The Library Class Model
480(3)
External Databases
483(4)
Result Set
484(1)
Relational Databases
485(2)
Presentation Objects
487(6)
Data Grids
488(1)
Charts
488(1)
Reports
489(1)
Hypercube Orientation
489(4)
Scripts
493(10)
Dimensional Calculation
494(9)
Activity Diagrams
503(4)
Cube Storage Management
503(4)
Translating Queries
507(8)
Summary
512(3)
Appendix A
515(72)
Market Leaders in Analytical Applications
516(1)
Vendor and Tools Summaries
517(1)
Brio Technology
518(5)
Company Background
518(1)
Product Background
519(4)
Conclusions
523(1)
Business Objects
523(6)
Company Background
523(1)
Product Background
524(3)
Conclusions
527(2)
Cognos
529(6)
Company Background
529(1)
Product Background
529(4)
Conclusions
533(2)
Hyperion Solutions
535(10)
Company Background
535(1)
Product Background
536(8)
Conclusions--HYPERION
544(1)
Arbor Background
545(12)
Conclusions--ARBOR
550(1)
Information Advantage
551(1)
Company Background
551(1)
Product Background
552(4)
Conclusions
556(1)
Informix
557(4)
Company Background
557(1)
Product Background
558(2)
Conclusions
560(1)
MicroStrategy
561(7)
Company Background
561(1)
Product Background
562(4)
Conclusions
566(2)
Oracle
568(7)
Company Background
568(1)
Applications
569(1)
Product Background
569(6)
Conclusions
575(1)
Microsoft Corporation
575(10)
Company Background
575(1)
Product Background
576(5)
Conclusions And Scores
581(1)
Microsoft OLAP Developments
582(3)
About The OLAP Report
585(1)
A Special Offer for Our Readers
586(1)
Glossary 587(24)
Index 611

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