properly disseminated, the change will not be reflected in some users’ data, resulting in decisions based on outdated information.

properly disseminated, the change will not be reflected in some users’ data, resulting in decisions based on outdated information.

Task-Data Dependency
Another problem with the flat-file approach is the user’s inability to obtain additional information as his or her needs change. This problem is called task-data

dependency. The user’s information set is constrained by the data that he or she possesses and controls. Users act independently rather than as members of a user

community. In such an environment, it is very difficult to establish a mechanism for the formal sharing of data. Therefore, new information needs tend to be satisfied

by procuring new data files. This takes time, inhibits performance, adds to data redundancy, and drives data management costs even higher.

Flat Files Limit Data Integration
The flat-file approach is a single-view model. Files are structured, formatted, and arranged to suit the specific needs of the owner or primary user of the data. Such

structuring, however, may exclude data attributes that are useful to other users, thus preventing successful integration of data across the organization. For example,

because the accounting function is the primary user of accounting data, these data are often captured, formatted, and stored to accommodate financial reporting and

GAAP. This structure, however, may be useless to the organization’s other (nonaccounting) users of accounting data, such as the marketing, finance, production, and

engineering functions. These users are presented with three options: (1) do not use accounting data to support decisions; (2) manipulate and massage the existing data

structure to suit their unique needs; or (3) obtain additional private sets of the data and incur the costs and operational problems associated with data redundancy.

In spite of these inherent limitations, many large organizations still use flat files for their general ledger and other financial systems. Most members of the data

processing community assumed that the end of the century would see the end of legacy systems. Instead, corporate America invested billions of dollars making these

systems year-2000 (Y2K) compliant. Legacy systems continue to exist because they add value for their users, and they will not be replaced until they cease to add

value. Students who may have to work with these systems in practice should be aware of their key features.

The Database Model
An organization can overcome the problems associated with flat files by implementing the database model to data management. Figure 1-13 illustrates how this approach

centralizes the organization’s data into a common database that is shared by other users. With the organization’s data in a central location, all users have access to

the data they need to achieve their respective objectives. Access to the data resource is controlled by a database management system (DBMS). The DBMS is a special

software system that is programmed to know which data elements each user is authorized to access. The user’s program sends requests for data to the DBMS, which

validates and authorizes access to the database in accordance with the user’s level of authority. If the user requests data that he or she is not authorized to access,

the request is denied. Clearly, the organization’s procedures for assigning user authority are an important control issue for auditors to consider. The most striking

difference between the database model and the flat-file model is the pooling of data into a common database that all organizational users share. With access to the

full domain of entity data, changes in user information needs can be satisfied without

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