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Chapter 3 • Data Warehousing 121

Tier 1: Tier 2:
Client workstation Application and
database server
figure 3.5 Architecture of a Two-Tier Data Warehouse.

architectures are known to be capable of serving the needs of large-scale, performance-
demanding information systems such as data warehouses. Referring to the use of n-tiered
architectures for data warehousing, Hoffer et al. (2007) distinguished among these archi-
tectures by dividing the data warehouse into three parts:

1. The data warehouse itself, which contains the data and associated software
2. Data acquisition (back-end) software, which extracts data from legacy systems and
external sources, consolidates and summarizes them, and loads them into the data
warehouse
3. Client (front-end) software, which allows users to access and analyze data from the
warehouse (a DSS/BI/business analytics [BA] engine)
In a three-tier architecture, operational systems contain the data and the software for
data acquisition in one tier (i.e., the server), the data warehouse is another tier, and the
third tier includes the DSS/BI/BA engine (i.e., the application server) and the client (see
Figure 3.4). Data from the warehouse are processed twice and deposited in an additional
multidimensional database, organized for easy multidimensional analysis and presenta-
tion, or replicated in data marts. The advantage of the three-tier architecture is its separa-
tion of the functions of the data warehouse, which eliminates resource constraints and
makes it possible to easily create data marts.
In a two-tier architecture, the DSS engine physically runs on the same hardware
platform as the data warehouse (see Figure 3.5). Therefore, it is more economical than
the three-tier structure. The two-tier architecture can have performance problems for large
data warehouses that work with data-intensive applications for decision support.
Much of the common wisdom assumes an absolutist approach, maintaining that
one solution is better than the other, despite the organization’s circumstances and unique
needs. To further complicate these architectural decisions, many consultants and software
vendors focus on one portion of the architecture, therefore limiting their capacity and
motivation to assist an organization through the options based on its needs. But these
aspects are being questioned and analyzed. For example, Ball (2005) provided deci-
sion criteria for organizations that plan to implement a BI application and have already
determined their need for multidimensional data marts but need help determining the
appropriate tiered architecture. His criteria revolve around forecasting needs for space
and speed of access (see Ball, 2005, for details).
Data warehousing and the Internet are two key technologies that offer important
solutions for managing corporate data. The integration of these two technologies pro-
duces Web-based data warehousing. In Figure 3.6, we show the architecture of Web-
based data warehousing. The architecture is three tiered and includes the PC client, Web
server, and application server. On the client side, the user needs an Internet connection
and a Web browser (preferably Java enabled) through the familiar graphical user inter-
face (GUI). The Internet/intranet/extranet is the communication medium between client

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