. Warehousing Success 426
Data Warehouse Architectures 428
Generic Two-Level Architecture 428
Independent Data Mart Data Warehousing Environment
426
429
C O NTENTS
Dependent Data Mart and Operational Data Store Architecture: A Three-Level Approach
Logical Data Mart and Real-Time Data Warehouse Architecture 432
Three-Layer Data Architecture 435
Role of the Enterprise Data Model 435
Role of Metadata 436
Some Characteristics of Data Warehouse Data
Status Versus Event Data 437
Transient Versus Periodic Data 438
An Example of Transient and Periodic Data 438
Transient Data 438
Periodic Data 439
Other Data VVarehouse Changes 440
The Reconciled Data Layer 441
Characteristics of Data after ETL 441
The ETL Process 442
Extract 442
Cleanse 444
Load and Index 446
Data Transformation 447
Data Transformation Functions 448
Record-Level Functions 448
Field-Level Functions 449
More Complex Transformations 451
Tools to Support Data Reconciliation 451
Data Quality Tools 451
Data Conversion Tools 452
Data Cleansing Tools 452
Selecting Tools 452
The Derived Data Layer 452
Characteristics of Derived Data 452
The Star Schema 453
Fact Tables and Dimension Tables 453
Example Star Schema 454
Surrogate Key 455
Grain of Fact Table 456
Duration of the Database 456
Size of the Fact Table 457
Modeling Date and Time 458
Variations of the Star Schema 458
Multiple Fact Tables 458
Factless Fact Tables 459
Normalizing Dimension Tables 460
Multivalued Dimensions 461
Hierarchies 461
Slowly Changing Dimensions 464
The User Interface 465
Role of Metadata 466
Querying Tools 466
Online Analytical Processing (OLAP) Tools
Slicing a Cube 468
Drill-Down 468
Data Mining Tools 469
Data Mining Techniques 469
Data Mining Applications 469
Data Visualization 470
