This chapter deals with auditing the systems that manage and control the organization’s data resource. Data management can be devided into two general approach : the flat-file model and the database model. The chapter opens with a description of flat-file data management , which is used in many older (legency) systems that are still in operation today. private ownership of data, which characterizes this model, is the root cause of several problems that inhabit data intergration. Then section present a conceptual overview of the database model and illustrates how problems associated with the flat-file model are resolved under this approach . the nations of entitywide data sharing and centralized control of data lie at the heart of the database philosophy

The chapter concludes with a discussion of the control and audit issues related to data management . the risks , audit objectives and audit procedures relevant to flat files, centralized databases and distributed databases are presented

Data management systems
There are two general approaches to data management : the flat-file model and the database model . the differences between the two approaches are both technical and philosophical. The defining features of each are presented below

a. the flat-file approach

the flat sile approach is most often associated with so-called legacy systems. These are large mainframe systems that were implemented in the late 1960s throught the 1980s. organization’s today still make extensive use of these systems . eventually , they will be replaced by modern database management systems but in the meantime , auditors must continued to deal with legacy systems technologies
the flat file model describe an environment in which individual data files are not related to others file. End users in this environment own their data files rather than share them with other users. Data processing is thus performed by standalone application rather than integrated systems.
When multiple users need the same data for different purpose, they must obtain separate data sets structured to their specific needs. Figure 3-1 illustrates how customers sales data might be presented to three different user in a durable organized by account number and structured to show outstanding balances. This is used for customer billing , account receivable maintenance, and financial statement prepation. Marketing needs customer sales history data organized by demographic keys for use in targeting new product promotion and for selling product uct and structured to show scheduled service dates. Such informations is used for marketing after-sales contact with customers to schedule preventive maintenance and t solicit sales of service agreement

Flat File Mo

User Standalone application User own data sets



Product Service

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