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The following scenario depicts what information systems looked like prior to the use of database
management systems. Imagine a physical office in which each person has his or her own file cabinet.
The information in the file cabinets belongs to the people whose desks are closest to them. They
decide what information will be in their file cabinets and how it will be organized. For example, sales
might refer to gross sales in one worker‟s cabinet and net sales in another‟s. Yet, the discrepancy
would be unimportant, because there was actually very little sharing of data.
Database management systems assume that information is a corporate asset to be shared by all
workers in the enterprise. Database technology, therefore, allows a company to have one integrated
location for the storage of all company data. These systems create a standard vocabulary, or data
dictionary, by which all references are consistent (e.g., “sales” always means “net sales”). They also
enable each user to have a personalized view of the data, as if the information was still in the file
cabinet next to the desk. Users need not concern themselves with the physical location or physical
order of the data, either. Database management systems are capable of presenting the data as
necessary. In fact, with distributed databases, the data does not even have to reside in the same
location or computer. It can be spread around the world if necessary. Database systems are sufficiently
intelligent and can find the data and process it as if it were located directly on the user‟s personal
computer.
Most of the software that was developed in the earlier years relied on data structures called flat files.
While some companies utilized database technology to store information, those database management
systems were, in many cases, unwieldy and very expensive both to acquire and to maintain. They were
usually hierarchical or network database systems, which were expensive and frequently required
special database administrators just to constantly fine-tune the system.
Today‟s database technology is based on a relational model, and, on a very simplistic basis, it
resembles a spreadsheet. In a relational database, there is a series of tables or files. Similar to a
spreadsheet table, each table has columns with attributes and rows of data. There can be an almost
unlimited number of tables in a database. While there is a practical limit to the size of a spreadsheet,
databases can contain thousands and thousands of columns and millions and millions of rows of data.
In addition, databases also allow users to relate or connect tables that share common columns of data.
Exhibit 20.7 is an example of a very simple portion of a payroll application. There are two different
tables. The employee table contains data about each of the company‟s employees: name, marital
status, number of dependents, and so on. The pay table contains data about every time each of the
employees is paid: their gross payroll, Social Security taxes, federal withholding, state tax, and so on.
First, notice the common column between the two tables, the employee number. This column
enables the database management system to relate the two tables. It allows the system, for example, to
print a payroll journal that has both the weekly payroll information from the pay table and to access
the employees‟ names from the employee table. Why not combine all the data into one table? Not only
would the employees‟ names and Social Security numbers appear multiple times, requiring the
unnecessary use of data storage, but also multiple versions of the truth might occur. If one of the
employees should happen to change her name, the database would show one name for part of the year
and another for the rest of the year. Redundant data creates opportunities for data corruption; just
because data is changed in one table, that same data is not necessarily changed in all tables. Prudent
systems design eliminates data field duplications wherever possible.