Data warehousing:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New Delhi
Oxford Univ. Press
2011
|
| Ausgabe: | 4. impr. |
| Schriftenreihe: | Oxford higher education
|
| Schlagworte: | |
| Online-Zugang: | Contributor biographical information Publisher description Table of contents only Inhaltsverzeichnis |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke Includes bibliographical references (p. [466]-469) and index |
| Beschreibung: | X, 474 S. 25 cm |
| ISBN: | 9780195699616 0195699610 |
Internformat
MARC
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| 490 | 0 | |a Oxford higher education | |
| 500 | |a Hier auch später erschienene, unveränderte Nachdrucke | ||
| 500 | |a Includes bibliographical references (p. [466]-469) and index | ||
| 650 | 4 | |a Data warehousing | |
| 650 | 4 | |a Data mining | |
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| 856 | 4 | |u http://www.loc.gov/catdir/enhancements/fy1013/2010483262-t.html |3 Table of contents only | |
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Datensatz im Suchindex
| _version_ | 1804143937343979520 |
|---|---|
| adam_text | Contents
Preface
Chapter
1:
Introduction to Data Warehousing
3
1.1
A Short Historical Note
4
1.2
Increasing Demand for Strategic Information
5
1.3
Data Warehouse Defined
10
1.4
Data Warehouse Users
14
1.5
Benefits of Data Warehousing
17
1.6
Concerns in Data Warehousing
19
Chapter
2:
Data Warehouse: Defining Features
23
2.1
Introduction
24
2.2
Features of a Data Warehouse
24
2.3
Data Granularity
31
2.4
The Information Flow Mechanism
33
2.5
Metadata
47
2.6
Two Classes of Data
52
2.7
The Lifecycle of Data
53
2.8
Data Flow from Warehouse to Operational Systems
56
Chapter
3:
Architecture of a Data Warehouse
61
3.1
Introduction
62
3.2
Characteristics of Data Warehouse Architecture
62
3.3
Data Warehouse Architecture Goals
65
3.4
Data Warehouse Architecture
65
3.5
Data Warehouse and Data Mart
73
3.6
Issues in Building Data Marts
74
3.7
Building Data Marts
79
3.8
Other Data Mart Issues
81
3.9
Increased Popularity of Data Marts
85
3.10
Can Data Warehouse and Data Mart Co-exist?
85
3.11
Pushing and Pulling Data
86
ГОД
Contents
Chapter
4:
Gathering the Business Requirements
91
4.1
Introduction
92
4.2
Determining the End-user Requirements
93
4.3
Requirements Gathering Methods
95
4.4
Requirements Analysis
102
4.5
Dimensional Analysis
203
4.6
Information Package Diagrams (IPD)
207
Chapter
5:
Planning and Project Management
114
5.1
Project Management Principles
125
5.2
Data Warehouse Readiness Assessment
227
5.3
Data Warehouse Project Team
220
5.4
Planning for the Data Warehouse
222
5.5
Data Warehouse Project Plan
224
5.6
Economic Feasibility Analysis
226
5.7
Planning for the Data Warehouse Server
230
5.8
Capacity Planning
235
5.9
Selecting the Operating System
240
5.10
Selecting the Database Software
242
5.11
Selecting the Tools
244
Chapter
6:
Data Warehouse Schema
155
6.1
Introduction
255
6.2
Dimensional Modelling
256
6.3
The Star Schema
25б
6.4
The Snowflake Schema
264
6.5
Aggregate Tables
269
6.6
Fact Constellation Schema
273
6.7
The Strengths of Dimensional Modelling
277
6.8
Data Warehouse and the Data Model
177
Chapter
7:
Dimensional Modelling
185
7.1
Characteristics of a Dimension Table
186
7.2
Characteristics of a Fact Table
187
7.3
The Factless Fact Table
189
7.4
Updates to the Dimension Tables
189
7.5
Cyclicity of Data—The Wrinkle of Time
295
7.6
Other Types of Dimension Tables
296
7.7
Keys in the Data Warehouse (Star) Schema
198
7.8
Enhancing the Data Warehouse Performance
200
7.9
Technology Requirements
224
Contents
Chapter
8:
The ETL Process
219
8.1
Introduction
220
8.2
Data Extraction
221
8.3
Data Transformation
229
8.4
Data Loading
232
8.5
Data Quality
237
Chapter
9:
Testing, Growth, and Maintenance
246
9.1
Data Warehouse Design Review
247
9.2
Developing the Data Warehouse Iteratively
250
9.3
Testing
250
9.4
Monitoring the Data Warehouse
256
9.5
Tuning the Data Warehouse
259
9.6
The Feedback Loop
262
Chapter
10: OLAP in
the Data Warehouse
266
10.1
Need For
OLAP 267
10.2 OLAP 269
10.3 OLAP
and Multidimensional Analysis
272
10.4 OLAP
Functions
276
10.5 OLAP
Applications
284
10.6 OLAP
Models
285
10.7 OLAP
Design Considerations
293
10.8 OLAP
Tools and Products
293
10.9
Existing
OLAP
Tools
295
10.10
Data Design
297
10.11
Administration and Performance
298
10.12 OLAP
Platforms
299
PART III
Chapter
11:
Building a Data Warehouse
305
11.1
Introduction
306
11.2
Problem Definition
306
11.3
Critical Success Factors
307
11.4
Requirement Analysis
309
11.5
Planning for the Data Warehouse
320
11.6
The Data Warehouse Design Stage
323
11.7
Building and Implementing Data Marts
327
11.8
Building Data Warehouses
327
11.9
Backup and Recovery
323
11.10
Establish the Data Quality Framework
325
11.12
Operating the Warehouse
327
11.13
Recipe for a Successful Warehouse
336
11.14
Data Warehouse Pitfalls
336
Contents
Chapter
12: Data Mining Basics 340
12.1
Introduction
342
12.2
Architecture of a Data Mining System
348
12.3
The Knowledge Discovery Process
349
12.4
Integrating Data Mining with Data Warehouse
352
12.5
Related Areas of Data Mining
356
12.6
Data Mining Techniques
357
Chapter
13:
Moving into Data Mining
379
13.1
Introduction
380
13.2
How Do We Categorize Data Mining Systems?
381
13.3
Interesting and Useful Data
382
13.4
Applications of Data Mining
383
13.5
Web Mining
392
13.6
Text Mining
395
13.7
Temporal Data Mining
396
13.8
Sequence Mining
399
13.9
Time-series Analysis
400
13.10
Spatial Data Mining
402
13.11
Issues and Challenges in Data Mining
404
13.12
Current Trends in Data Mining
405
Chapter
14:
Trends in Data Warehousing
410
14.1
Introduction
411
14.2
Data Warehouse Solutions
422
14.3
Web-enabled Data Warehouse
426
14.4
Distributed Data Warehouse
427
14.5
Virtual Data Warehouse
430
14.6
Operational Data Store
434
14.7
Integration with Other Technologies
438
14.8
Trends in Data Warehousing
447
14.9
Data Warehouse Futures
452
Glossary
457
Bibliography
466
Index
470
|
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