THE DATABASE MANAGEMENT SYSTEM CONCEPT - Fundamentals of Database Management Systems - page 50

positive feature of a database management system. Data redundancy is a negative
feature (except for performance reasons under certain circumstances that will be
discussed later in this topic).

In terms of the data structures used in database management systems, data
integration and data redundancy are tied together and will be discussed together in
this section of the topic.
Data stored in an information system describes the real-world business
environment. Put another way, the data is a reflection of the environment. Over the
years that information systems have become increasingly sophisticated, they and
the data that they contain have revolutionized the ways that we conduct virtually
all aspects of business. But, as valuable as the data is, if the data is duplicated
and stored multiple times within a company's information systems facilities, it can
result in a nightmare of poor performance, lack of trust in the accuracy of the data,
and a reduced level of competitiveness in the marketplace. Data redundancy and
the problems it causes can occur within a single file or across multiple files. The
problems caused by data redundancy are threefold:

First, the redundant data takes up a great deal of extra disk space. This alone can
be quite significant.

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Second, if the redundant data has to be updated, additional time is needed to do
so since, if done correctly, every copy of the redundant data must be updated.
This can create a major performance issue.

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Third and potentially the most significant is the potential for data integrity
problems. The term data integrity refers to the accuracy of the data. Obviously,
if the data in an information system is inaccurate, it and the whole information
system are of limited value. The problem with redundant data, whether in a single
file or across multiple files, occurs when it has to be updated (or possibly when
it is first stored). If data is held redundantly and all the copies of the data record
being updated are not all correctly updated to the new values, there is clearly
a problem in data integrity. There is an old saying that has some applicability
here, ''The person with one watch always knows what time it is. The person with
several watches is never quite sure,'' Figure 3.4.

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Data Redundancy AmongMany Files Beginning with data redundancy across multiple
files, consider the following situation involving customer names and addresses.
Frequently, different departments in an enterprise in the course of their normal
everyday work need the same data. For example, the sales department, the accounts
receivable department, and the credit department may need customer name and

FIGURE 3.4
With several watches the correct time
might not be clear