Data warehousing fundamentals: a comprehensive guide for IT professionals
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York [u.a.]
Wiley
2001
|
| Series: | A Wiley-Interscience publication
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXV, 516 S. Ill., graph Darst. |
| ISBN: | 0471412546 |
Staff View
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Record in the Search Index
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|---|---|
| adam_text | CONTENTS
Foreword xxi
Preface xxiii
Part 1 OVERVIEW AND CONCEPTS
1 The Compelling Need for Data Warehousing 1
Chapter Objectives 1
Escalating Need for Strategic Information 2
The Information Crisis 3
Technology Trends 4
Opportunities and Risks 5
Failures of Past Decision Support Systems 7
History of Decision Support Systems 8
Inability to Provide Information 9
Operational Versus Decision Support Systems 9
Making the Wheels of Business Turn 10
Watching the Wheels of Business Turn 10
Different Scope, Different Purposes 10
Data Warehousing—The Only Viable Solution 12
A New Type of System Environment 12
Processing Requirements in the New Environment 12
Business Intelligence at the Data Warehouse 12
Data Warehouse Defined 13
A Simple Concept for Information Delivery 14
vii
Viii CONTENTS
An Environment, Not a Product 14
A Blend of Many Technologies 14
Chapter Summary 15
Review Questions 16
Exercises 16
2 Data Warehouse: The Building Blocks 19
Chapter Objectives 19
Defining Features 20
Subject Oriented Data 20
Integrated Data 21
Time Variant Data 22
Nonvolatile Data 23
Data Granularity 23
Data Warehouses and Data Marts 24
How are They Different? 25
Top Down Versus Bottom Up Approach 26
A Practical Approach 27
Overview of the Components 28
Source Data Component 28
Data Staging Component 31
Data Storage Component 33
Information Delivery Component 34
Metadata Component 35
Management and Control Component 35
Metadata in the Data Warehouse 35
Types of Metadata 36
Special Significance 36
Chapter Summary 36
Review Questions 37
Exercises 37
3 Trends in Data Warehousing 39
Chapter Objectives 39
Continued Growth in Data Warehousing 40
Data Warehousing is Becoming Mainstream 40
Data Warehouse Expansion 41
Vendor Solutions and Products 42
Significant Trends 43
Multiple Data Types 44
Data Visualization 46
Parallel Processing 48
CONTENTS iX
Query Tools 49
Browser Tools 50
Data Fusion 50
Multidimensional Analysis 51
Agent Technology 51
Syndicated Data 52
Data Warehousing and ERP 52
Data Warehousing and KM 53
Data Warehousing and CRM 54
Active Data Warehousing 56
Emergence of Standards 56
Metadata 57
OLAP 57
Web Enabled Data Warehouse 58
The Warehouse to the Web 59
The Web to the Warehouse 59
The Web Enabled Configuration 60
Chapter Summary 61
Review Questions 61
Exercises 62
Part 2 PLANNING AND REQUIREMENTS
4 Planning and Project Management 63
Chapter Objectives 63
Planning Your Data Warehouse 64
Key Issues 64
Business Requirements, Not Technology 66
Top Management Support 67
Justifying Your Data Warehouse 67
The Overall Plan 68
The Data Warehouse Project 69
How is it Different? 70
Assessment of Readiness 71
The Life Cycle Approach 71
The Development Phases 73
The Project Team 74
Organizing the Project Team 75
Roles and Responsibilities 75
Skills and Experience Levels 77
User Participation 78
Project Management Considerations 80
Guiding Principles 81
X CONTENTS
Warning Signs 82
Success Factors 82
Anatomy of a Successful Project 83
Adopt a Practical Approach 84
Chapter Summary 86
Review Questions 86
Exercises 87
5 Defining the Business Requirements 89
Chapter Objectives 89
Dimensional Analysis 90
Usage of Information Unpredictable 90
Dimensional Nature of Business Data 90
Examples of Business Dimensions 92
Information Packages—A New Concept 93
Requirements Not Fully Determinate 93
Business Dimensions 95
Dimension Hierarchies/Categories 95
Key Business Metrics or Facts 96
Requirements Gathering Methods 97
Interview Techniques 99
Adapting the JAD Methodology 102
Review of Existing Documentation 103
Requirements Definition: Scope and Content 104
Data Sources 105
Data Transformation 105
Data Storage 105
Information Delivery 105
Information Package Diagrams 106
Requirements Definition Document Outline 106
Chapter Summary 106
Review Questions 107
Exercises 107
6 Requirements as the Driving Force for Data Warehousing 109
Chapter Objectives 109
Data Design 110
Structure for Business Dimensions 112
Structure for Key Measurements 112
Levels of Detail 113
The Architectural Plan 113
Composition of the Components 114
CONTENTS Xi
Special Considerations 115
Tools and Products 118
Data Storage Specifications 119
DBMS Selection 120
Storage Sizing 120
Information Delivery Strategy 121
Queries and Reports 122
Types of Analysis 123
Information Distribution 123
Decision Support Applications 123
Growth and Expansion 123
Chapter Summary 124
Review Questions 124
Exercises 125
Part 3 ARCHITECTURE AND INFRASTRUCTURE
7 The Architectural Components 127
Chapter Objectives 127
Understanding Data Warehouse Architecture 127
Architecture: Definitions 127
Architecture in Three Major Areas 128
Distinguishing Characteristics 129
Different Objectives and Scope 130
Data Content 130
Complex Analysis and Quick Response 131
Flexible and Dynamic 131
Metadata driven 132
Architectural Framework 132
Architecture Supporting Flow of Data 132
The Management and Control Module 133
Technical Architecture 134
Data A cquisition 135
Data Storage 138
Information Delivery 140
Chapter Summary 142
Review Questions 142
Exercises 143
8 Infrastructure as the Foundation for Data Warehousing 145
Chapter Objectives 145
Infrastructure Supporting Architecture 145
XM CONTENTS
Operational Infrastructure 147
Physical Infrastructure 147
Hardware and Operating Systems 148
Platform Options 150
Server Hardware 158
Database Software 164
Parallel Processing Options 164
Selection of the DBMS 166
Collection of Tools 167
Architecture First, Then Tools 168
Data Modeling 169
Data Extraction 169
Data Transformation 169
Data Loading 169
Data Quality 169
Queries and Reports 170
Online Analytical Processing (OLAP) 170
Alert Systems 170
Middleware and Connectivity 170
Data Warehouse Management 170
Chapter Summary 170
Review Questions 171
Exercises 171
9 The Significant Role of Metadata 173
Chapter Objectives 173
Why Metadata is Important 173
A Critical Need in the Data Warehouse 175
Why Metadata is Vital for End Users 177
Why Metadata is Essential for IT 179
Automation ofWarehousing Tasks 181
Establishing the Context of Information 183
Metadata Types by Functional Areas 183
Data Acquisition 184
Data Storage 186
Information Delivery 186
Business Metadata 187
Content Overview 188
Examples of Business Metadata 188
Content Highlights 189
Who Benefits? 190
Technical Metadata 190
CONTENTS XiH
Content Overview 190
Examples of Technical Metadata 191
Content Highlights 192
Who Benefits? 192
How to Provide Metadata 193
Metadata Requirements 193
Sources of Metadata 194
Challenges for Metadata Management 196
Metadata Repository 196
Metadata Integration and Standards 198
Implementation Options 199
Chapter Summary 200
Review Questions 201
Exercises 201
Part 4 DATA DESIGN AND DATA PREPARATION
10 Principles of Dimensional Modeling 203
Chapter Objectives 203
From Requirements to Data Design 203
Design Decisions 204
Dimensional Modeling Basics 204
E R Modeling Versus Dimensional Modeling 209
Use of CASE Tools 209
The STAR Schema 210
Review of a Simple STAR Schema 210
Inside a Dimension Table 212
Inside the Fact Table 214
The Factless Fact Table 216
Data Granularity 217
STAR Schema Keys 218
Primary Keys 218
Surrogate Keys 219
Foreign Keys 219
Advantages of the STAR Schema 220
Easy for Users to Understand 220
Optimizes Navigation 221
Most Suitable for Query Processing 222
STARjoin and STARindex 223
Chapter Summary 223
Review Questions 224
Exercises 224
XJV CONTENTS
11 Dimensional Modeling: Advanced Topics 225
Chapter Objectives 225
Updates to the Dimension Tables 226
Slowly Changing Dimensions 226
Type 1 Changes: Correction of Errors 227
Type 2 Changes: Preservation of History 228
Type 3 Changes: Tentative Soft Revisions 230
Miscellaneous Dimensions 231
Large Dimensions 231
Rapidly Changing Dimensions 233
Junk Dimensions 235
The Snowflake Schema 235
Options to Normalize 235
Advantages and Disadvantages 238
When to Snowflake 238
Aggregate Fact Tables 239
Fact Table Sizes 241
Need for Aggregates 242
Aggregating Fact Tables 243
Aggregation Options 247
Families of STARS 249
Snapshot and Transaction Tables 250
Core and Custom Tables 251
Supporting Enterprise Value Chain or Value Circle 251
Conforming Dimensions 253
Standardizing Facts 254
Summary of Family of STARS 254
Chapter Summary 255
Review Questions 255
Exercises 256
12 Data Extraction, Transformation, and Loading 257
Chapter Objectives 257
ETL Overview 258
Most Important and Most Challenging 259
Time consuming and Arduous 260
ETL Requirements and Steps 260
Key Factors 261
Data Extraction 262
Source Identification 263
Data Extraction Techniques 263
Evaluation of the Techniques 270
CONTENTS XV
Data Transformation 271
Data Transformation: Basic Tasks 272
Major Transformation Types 273
Data Integration and Consolidation 275
Transformation for Dimension Attributes 277
How to Implement Transformation 277
Data Loading 279
Applying Data: Techniques and Processes 280
Data Refresh Versus Update 282
Procedure for Dimension Tables 283
Fact Tables: History and Incremental Loads 284
ETL Summary 285
ETL Tool Options 285
Reemphasizing ETL Metadata 286
ETL Summary and Approach 287
Chapter Summary 288
Review Questions 288
Exercises 289
13 Data Quality: A Key to Success 291
Chapter Objectives 291
Why is Data Quality Critical? 292
What is Data Quality? 292
Benefits of Improved Data Quality 295
Types of Data Quality Problems 296
Data Quality Challenges 299
Sources of Data Pollution 299
Validation of Names and Addresses 301
Costs of Poor Data Quality 302
Data Quality Tools 303
Categories of Data Cleansing Tools 303
Error Discovery Features 303
Data Correction Features 303
The DBMS for Quality Control 304
Data Quality Initiative 304
Data Cleansing Decisions 305
Who Should be Responsible? 307
The Purification Process 309
Practical Tips on Data Quality 311
Chapter Summary 311
Review Questions 312
Exercises 312
XVi CONTENTS
Part 5 INFORMATION ACCESS AND DELIVERY
14 Matching Information to the Classes of Users 315
Chapter Objectives 315
Information from the Data Warehouse 316
Data Warehouse Versus Operational Systems 316
Information Potential 318
User Information Interface 321
Industry Applications 323
Who Will Use the Information? 323
Classes of Users 323
What They Need 326
How to Provide Information 329
Information Delivery 329
Queries 331
Reports 332
Analysis 333
Applications 334
Information Delivery Tools 335
The Desktop Environment 335
Methodology for Tool Selection 335
Tool Selection Criteria 338
Information Delivery Framework 340
Chapter Summary 341
Review Questions 341
Exercises 341
15 OLAP in the Data Warehouse 343
Chapter Objectives 343
Demand for Online Analytical Processing 344
Need for Multidimensional Analysis 344
Fast Access and Powerful Calculations 345
Limitations of Other Analysis Methods 347
OLAP is the Answer 349
OLAP Definitions and Rules 349
OLAP Characteristics 352
Major Features and Functions 353
General Features 353
Dimensional Analysis 353
What are Hypercubes? 357
Drill Down and Roll Up 360
Slice and Dice or Rotation 362
CONTENTS XVH
Uses and Benefits 363
OLAP Models 363
Overview of Variations 364
The MOLAP Model 365
The ROLAP Model 366
ROLAP Versus MOLAP 367
OLAP Implementation Considerations 368
Data Design and Preparation 368
Administration and Performance 370
OLAP Platforms 372
OLAP Tools and Products 3 73
Implementation Steps 374
Chapter Summary 374
Review Questions 374
Exercises 375
16 Data Warehousing and the Web 377
Chapter Objectives 377
Web Enabled Data Warehouse 378
Why the Web? 378
Convergence of Technologies 380
Adapting the Data Warehouse for the Web 381
The Web as a Data Source 382
Web Based Information Delivery 383
Expanded Usage 383
New Information Strategies 385
Browser Technology for the Data Warehouse 387
Security Issues 389
OLAP and the Web 389
Enterprise OLAP 389
Web OLAP Approaches 390
OLAP Engine Design 390
Building a Web Enabled Data Warehouse 391
Nature of the Data Webhouse 391
Implementation Considerations 393
Putting the Pieces Together 394
Web Processing Model 394
Chapter Summary 396
Review Questions 396
Exercises 396
xviii contents
17 Data Mining Basics 399
Chapter Objectives 399
What is Data Mining? 400
Data Mining Defined 401
The Knowledge Discovery Process 402
OLAP Versus Data Mining 404
Data Mining and the Data Warehouse 406
Major Data Mining Techniques 408
Cluster Detection 409
Decision Trees 411
Memory Based Reasoning 413
LinkAnalysis 415
Neural Networks 417
Genetic Algorithms 418
Moving into Data Mining 419
Data Mining Applications 422
Benefits of Data Mining 423
Applications in Retail Industry 424
Applications in Telecommunications Industry 425
Applications in Banking and Finance 426
Chapter Summary 426
Review Questions 426
Exercises 427
Part 6 IMPLEMENTATION AND MAINTENANCE
18 The Physical Design Process 429
Chapter Objectives 429
Physical Design Steps 430
Develop Standards 430
Create Aggregates Plan 431
Determine the Data Partitioning Scheme 431
Establish Clustering Options 432
Prepare an Indexing Strategy 432
Assign Storage Structures 432
Complete Physical Model 433
Physical Design Considerations 433
Physical Design Objectives 433
From Logical Model to Physical Model 434
Physical Model Components 435
Significance of Standards 436
Physical Storage 438
CONTENTS XJX
Storage Area Data Structures 439
Optimizing Storage 440
Using RAID Technology 442
Estimating Storage Sizes 442
Indexing the Data Warehouse 443
Indexing Overview 443
B Tree Index 445
Bitmapped Index 446
Clustered Indexes 448
Indexing the Fact Table 448
Indexing the Dimension Tables 449
Performance Enhancement Techniques 449
Data Partitioning 449
Data Clustering 450
Parallel Processing 450
Summary Levels 451
Referential Integrity Checks 451
Initialization Parameters 451
Data Arrays 452
Chapter Summary 452
Review Questions 452
Exercises 453
19 Data Warehouse Deployment 455
Chapter Objectives 455
Major Deployment Activities 456
Complete User Acceptance 456
Perform Initial Loads 45 7
Get User Desktops Ready 458
Complete Initial User Training 459
Institute Initial User Support 460
Deploy in Stages 460
Considerations for a Pilot 462
When Is a Pilot Data Mart Useful? 462
Types of Pilot Projects 463
Choosing the Pilot 465
Expanding and Integrating the Pilot 466
Security 467
Security Policy 467
Managing User Privileges 468
Password Considerations 469
Security Tools 469
XX CONTENTS
Backup and Recovery 470
Why Back Up the Data Warehouse? 470
Backup Strategy 471
Setting Up a Practical Schedule 472
Recovery 472
Chapter Summary 473
Review Questions 474
Exercises 474
20 Growth and Maintenance 477
Chapter Objectives 477
Monitoring the Data Warehouse 478
Collection of Statistics 478
Using Statistics for Growth Planning 480
Using Statistics for Fine Tuning 480
Publishing Trends for Users 481
User Training and Support 481
User Training Content 482
Preparing the Training Program 482
Delivering the Training Program 484
User Support 485
Managing the Data Warehouse 487
Platform Upgrades 487
Managing Data Growth 488
Storage Management 488
ETL Management 489
Data Model Revisions 489
Information Delivery Enhancements 489
Ongoing Fine Tuning 490
Chapter Summary 490
Review Questions 491
Exercises 491
Appendix A. Project Life Cycle Steps and Checklists 493
Appendix B. Critical Factors for Success 497
Appendix C. Guidelines for Evaluating Vendor Solutions 499
References 501
Glossary 503
Index 511
|
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| language | English |
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| spelling | Ponniah, Paulraj Verfasser aut Data warehousing fundamentals a comprehensive guide for IT professionals Paulraj Ponniah New York [u.a.] Wiley 2001 XXV, 516 S. Ill., graph Darst. txt rdacontent n rdamedia nc rdacarrier A Wiley-Interscience publication Data-Warehouse-Konzept (DE-588)4406462-7 gnd rswk-swf Data-Warehouse-Konzept (DE-588)4406462-7 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009556087&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ponniah, Paulraj Data warehousing fundamentals a comprehensive guide for IT professionals Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| subject_GND | (DE-588)4406462-7 |
| title | Data warehousing fundamentals a comprehensive guide for IT professionals |
| title_auth | Data warehousing fundamentals a comprehensive guide for IT professionals |
| title_exact_search | Data warehousing fundamentals a comprehensive guide for IT professionals |
| title_full | Data warehousing fundamentals a comprehensive guide for IT professionals Paulraj Ponniah |
| title_fullStr | Data warehousing fundamentals a comprehensive guide for IT professionals Paulraj Ponniah |
| title_full_unstemmed | Data warehousing fundamentals a comprehensive guide for IT professionals Paulraj Ponniah |
| title_short | Data warehousing fundamentals |
| title_sort | data warehousing fundamentals a comprehensive guide for it professionals |
| title_sub | a comprehensive guide for IT professionals |
| topic | Data-Warehouse-Konzept (DE-588)4406462-7 gnd |
| topic_facet | Data-Warehouse-Konzept |
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