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Q3 How Do Organizations Use Data Warehouses and Data Marts to Acquire Data? 349

analysis indicates it will be sacrificing little revenue to do so. Or it might do it as a PR move
intended to show that it’s on top of the latest manufacturing technology. Or it might decide to
postpone consideration of 3D printing because it doesn’t see that many customers ordering the
qualifying parts.
Of course, there is the possibility that Addison and Drew chose the wrong criteria. If they
have time, it might be tempting for Addison and Drew to change their criteria and repeat the
analysis. Such a course is a slippery slope, however. They might find themselves changing crite-
ria until they obtain a result they want, which yields a very biased study.
This possibility points again to the importance of the human component of an IS. The hard-
ware, software, data, and query-generation procedures are of little value if the decisions that
Addison and Drew made when setting and possibly revising criteria are poor. Business intel-
ligence is only as intelligent as the people creating it!
With this example in mind, we will now consider each of the activities in Figure 9-3 in
greater detail.

Q3 How Do Organizations Use Data Warehouses

and Data Marts to Acquire Data?

Although it is possible to create basic reports and perform simple analyses from operational
data, this course is not usually recommended. For reasons of security and control, IS profes-
sionals do not want employees like Addison processing operational data. If Addison makes
an error, that error could cause a serious disruption in AllRoad’s operations. Also, opera-
tional data is structured for fast and reliable transaction processing. It is seldom structured
in a way that readily supports BI analysis. Finally, BI analyses can require considerable
processing; placing BI applications on operational servers can dramatically reduce system
performance.
For these reasons, most organizations extract operational data for BI processing. For a
small organization like AllRoad, the extraction may be as simple as an Access database. Larger
organizations, however, typically create and staff a group of people who manage and run a data
warehouse, which is a facility for managing an organization’s BI data. The functions of a data
warehouse are to:

• Obtain data
• Cleanse data
• Organize and relate data
• Catalog data
Figure 9-12 shows the components of a data warehouse. Programs read operational and
other data and extract, clean, and prepare that data for BI processing. The prepared data is
stored in a data warehouse database using a data warehouse DBMS, which can be different from
the organization’s operational DBMS. For example, an organization might use Oracle for its
operational processing, but use SQL Server for its data warehouse. Other organizations use SQL
Server for operational processing, but use DBMSs from statistical package vendors such as SAS
or SPSS in the data warehouse.
Collecting and selling data about Data warehouses include data that is purchased from outside sources. The purchase of
consumer shopping habits is big data about organizations is not unusual or particularly concerning from a privacy standpoint.
business. But what information However, some companies choose to buy personal consumer data (e.g., marital status) from
about you is being collected?
And how is it being used? The data vendors such as Acxiom Corporation. Figure 9-13 lists some of the consumer data that can
Ethics Guide on pages 354-355 be readily purchased. An amazing (and, from a privacy standpoint, frightening) amount of data
considers these questions. is available.