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Online analytical processing (OLAP) is a powerful tool for end users to use to access data. As
discussed earlier, the data (the facts) is stored with its characteristics (called dimensions). The concept
uses a cube as a visual to the end user. Of course, a cube can‟t be stored as such on a hard drive. The
data for OLAP retrieval is stored using either a star schema or a snowflake schema. A star schema
would include only the primary dimensions and fact table. When we expand our dimensions to include
further details about the dimensions, the schema becomes more complicated—a snowflake schema.
Illustrated in Exhibit 20.8 is the snowflake schema for the example used earlier in Exhibit 20.4.
New technologies have been developed to address the issue of information overload. In the 1970s,
the average database was perhaps 100 megabytes in size. In the 1980s, databases were typically 20
gigabytes. Now, databases are in terabytes (trillions of bytes). Wal-Mart has a data warehouse that
exceeds 4 petabytes (a petabype is a quadrillion bytes or 1,024 terabytes). With all that data, it is
difficult for a user to know where to look. It is not the question that the user knows to ask that is
necessarily important, but, rather, the question that the user does not know to ask that will come back
to haunt him.
Data mining is a set of technologies that allow users to classify, cluster, learn about associations,
and perform regressions. Classification uses algorithms to assign data into a predefined group.
Clustering is similar to classification but the groups are not predefined. Regression analyzes the data
to build a model that can be used for forecasting. Learning about associations searches for
relationships between variables. Market basket analysis is used by supermarkets to analyze the data of
what each customer buys to determine what products are frequently bought together. Data mining is
used in customer relationship management software to identify prospects with a higher likelihood to
respond to an offer.
Data mining can also be used to scan databases for any data that does not fit the business‟s model
and identify any data that the user needs to examine further. For example, auditors might use data
mining to scan client transaction detail to look for transactions that do not conform to company
policies, and stock analysts can use it to scan data on stock prices and company earnings over a period
of time in order to look for opportunities.
Internet Technology
Nothing has impacted technology and society in the past two decades more than the Internet. When
Bill Clinton was inaugurated in January 1993, there were about 50 pages on the Internet. Today, there
are more than 200 billion pages (and that‟s only an estimate—it‟s probably much higher than that!).
The underlying technology behind the Internet has its roots in a project begun by the U.S. government