The document discusses the components and architectures of data warehousing systems. It describes the major components as including data sources, extraction, loading, a comprehensive database, and metadata. It outlines three common architectures: three-tier, two-tier, and web-based. It also discusses alternative architectures and factors to consider when deciding which architecture to use, such as the database system, parallel processing, data migration tools, and data retrieval/analysis tools.

2. 2

3.  The major components of a data
warehousing process
 Data sources
 Data extraction
 Data loading
 Comprehensive database
 Metadata
 Middleware tools
3

4. 4

5.  Three parts of the data warehouse
 The data warehouse that contains the data and
associated software
 Data acquisition (back-end) software that extracts
data from legacy systems and external sources,
consolidates and summarizes them, and loads
them into the data warehouse
 Client (front-end) software that allows users to
access and analyze data from the warehouse
5

6. Architecture of a three-tier
data warehouse
6

7. Architecture of a two tier data
warehouse
7

8. Architecture of web based data warehousing.
8

9.  Issues to consider when deciding which
architecture to use:
 Which database management system (DBMS) should
be used?
 Will parallel processing and/or partitioning be used?
 Will data migration tools be used to load the data
warehouse?
 What tools will be used to support data retrieval and
analysis?

10. Alternative Data Warehouse Architectures:
• EDW Architecture
10

11. Alternative Data Warehouse Architectures:
• Data Mart Architecture
11

12. Alternative Data Warehouse Architectures:
• Hub-and-Spoke Data Mart Architecture
12

13. Alternative Data Warehouse Architectures:
• EDW and ODS (real time access support)
13

14. Alternative Data Warehouse Architectures:
•Distributed Data Warehouse Architecture
14

15. Alternative Architectures for Data Warehouse Efforts
15

16. Teradata Corp.’s EDW
16

17. Ten factors that potentially affect the architecture selection
decision:
1. Information 5. Constraints on resources
interdependence between 6. Strategic view of the data
organizational units warehouse prior to
2. Upper management’s implementation
information needs 7. Compatibility with existing
3. Urgency of need for a data systems
warehouse 8. Perceived ability of the in-
4. Nature of end-user tasks house IT staff
9. Technical issues
10. Social/political factors

18.  DECISION SUPPORT SYSTEMS AND
BUSINESS INTELLIGENCE. Turban
 Modern Data Warehousing, Mining, and
Visualization: Core Concepts. George M.
Marakas
 Modern Database Management.9th
Edition.Jeffrey A. Hoffer, Mary B. Prescott,
Heikki Topi