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Data Access and OLAP<br />

Before the late 1980s, data in databases was accessible only via code that was typically written by a<br />

programmer in the IT organization. As database management software evolved to create user-friendly<br />

interfaces for building retrieval code, users began to build their own queries. (A query is an<br />

interrogation of data found in a database.) Rather than completely specify what data they wanted to<br />

see and how they wanted to see it formatted and then waiting for IT staff to get to the request (and<br />

there always seems to be a backlog), users could use a template or wizard to select their data and<br />

review the results, modify their request, review the results, and continue until the results were what<br />

they needed and were formatted appropriately.<br />

Most databases used in organizations today are relational, and these queries are actually in<br />

Structured Query Language (SQL) code that is used against the database. More on SQL and relational<br />

databases can be found in the database section later in the chapter.<br />

Organizations have begun to separate their operational data from their business intelligence data.<br />

The BI data are regularly written to the firm‟s data warehouse. Details as to how that process happens<br />

are discussed later in this chapter. Important to understand at this point is how a user can access this<br />

large volume of data that has been formatted to support business intelligence.<br />

One important tool for BI is Online Analytical Processing (OLAP), which presents data as a virtual<br />

cube (think of a Rubik‟s cube) for analysis. The data could actually have more than three dimensions,<br />

but in practice the visual is still referred to as a cube. The facts from operational systems is the data<br />

that are stored in the cube. The cube‟s dimensions are the categories of the data. An analyst can pick<br />

the dimensions that are of interest, and the software aggregates (such as average, count, sum,<br />

maximum, minimum) the remaining dimension within seconds.<br />

Exhibit 20.3 Business intelligence cube for actual sales.

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