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Chapter 6 Foundations of Business Intelligence: Databases and Information Management 257

FIGURE 6.12 COMPONENTS OF A DATA WAREHOUSE

A contemporary business intelligence infrastructure features capabilities and tools to manage and
analyze large quantities and different types of data from multiple sources. Easy-to-use query and
reporting tools for casual business users and more sophisticated analytical toolsets for power users
are included.

that’s been restructured and reorganized for reporting and analysis. Hadoop
clusters pre-process big data for use in the data warehouse, data marts, or an
analytic platform, or for direct querying by power users. Outputs include reports
and dashboards as well as query results. Chapter 12 discusses the various types of
BI users and BI reporting in greater detail.

ANALYTICAL TOOLS: RELATIONSHIPS, PATTERNS,
TRENDS

Once data have been captured and organized using the business intelligence
technologies we have just described, they are available for further analysis using
software for database querying and reporting, multidimensional data analysis
(OLAP), and data mining. This section will introduce you to these tools, with
more detail about business intelligence analytics and applications in Chapter 12.

Online Analytical Processing (OLAP)
Suppose your company sells four different products—nuts, bolts, washers, and
screws—in the East, West, and Central regions. If you wanted to ask a fairly
straightforward question, such as how many washers sold during the past
quarter, you could easily find the answer by querying your sales database.
But what if you wanted to know how many washers sold in each of your sales
regions and compare actual results with projected sales?
To obtain the answer, you would need online analytical processing (OLAP).
OLAP supports multidimensional data analysis, enabling users to view the same

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