Data Warehousing Fundamentals for IT Professionals

INDEX

Additive measures, 237

Agent technology, 59

Aggregates

fact tables, 266–270

need for, 266

Aggregation

goals, 271

options, 271–272

suggestions for, 271–272

Alert systems, 188

Analysis, 359

Analytical processing, see OLAP

Applications, 359–360

Architecture, 141–160

characteristics of, 143–146

definitions for, 141–142

framework, 146–148

in major areas, 142–143

technical, 148–156

types of

centralized, 32, 156

data-mart bus, 32, 160

federated, 33, 159

hub-and-spoke, 33, 159

independent data marts, 34, 156

Archived data, 36

Backup, see also Recovery

reasons for, 505

schedule, 506–507

strategy, 505–506

Best practices, real-world examples of,

airlines, 549

credit union, 552–553

health care, 550

home improvement retail, 552

international shipping and delivery, 551

life insurance, 553

phone service, 552

rail services, 551

securities, 551

specialty textiles, 550

telecommunications, 553

travel, 550

Bitmapped index, 481–482. See also Indexing

Bottom-up approach, 30–31

Browser, Web, 418–419

B-Tree index, 479–480. See also Indexing

Business data, dimensional nature of, 101–102

Business dimensions

examples of, 102–103

hierarchies, 106–107

Business intelligence

evolution of, 18–19

two environments, 19

Business metrics, 107

Business requirements, see Requirements

CASE tools, 232

Categories, in dimensions, 106–107

Checkpoint, for data loads, 493

Cleansing, see Data cleansing

Client/server architecture, 174–175

Cluster detection, in data mining, 440–443

Clustered indexes, 482

Clustering, 466 ...