Accounting Information System

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1. What is data vis-à-vis information? When can information be deemed good and useful? How are these related/ connected to an information system? Data are facts, which may or may not be processed (edited, summarized, or refined) and have no direct effect on the user. By contrast, information causes the user to take an action that he or she otherwise could not, or would not, have taken. Information is often defined simply as processed data. This is an inadequate definition. Information is determined by the effect it has on the user, not by its physical form. We also say that information is not just a set of processed facts arranged in a formal report. Information allows user to take action to resolve conflicts, reduce uncertainty, and make decisions. We should note that action does not necessarily mean a physical act. The distinction between data and information has a pervasive implication for the study of information systems. If output from the information system fails to cause users to act, the system serves no purpose and has failed in its primary objectives. 2. Is there any general ruling governing when data is being collected? What are levels of data hierarchy? Data sources are financial transactions that enter the information system from both internal and external sources. External financial transactions are the most common source of data for most organizations. These are economic exchanges with other business entities and individuals outside the firm. Internal financial transactions involve the exchange or movement of resources within the organization. Data Collection is the first operational stage in the information system. The objective is to ensure that event data entering the system are valid, complete, and free from material errors. In many respects, this is the most important stage in the system. Should the transaction errors pass through data collection undetected, the system may process the errors and generate erroneous and unreliable output. This, in turn, could lead to incorrect actions and poor decisions by the users. Two rules govern the design of data collection procedures: relevance and efficiency. The information system should capture only relevant data. A fundamental task of the system designer is to determine what is and what is not relevant. The data collection stage should be designed to filter irrelevant facts from the system. Efficient data collection procedures are designed to collect data only once. These data can then be made available to multiple users. Capturing the same data more than once leads to data redundancy and inconsistency. Information systems have limited collection, processing and data storage capacity. Data redundancy overloads facilities and reduces the overall efficiency of the system. Inconsistency among redundant data elements can result in inappropriate actions and bad decisions. Data processing, once collected, data usually require processing to produce information. Tasks in the data processing sage range from simple to complex. Database management, the organization’s database is its physical repository for financial and nonfinancial data. We use the term database in the generic sense. It can be filing cabinet or a computer disk. Regardless of the database’s physical form, we can represent its contents in a logical hierarchy. In hierarchy there is data attribute; data attribute is the most elemental piece of potentially useful in the database. An attribute is a logical and relevant characteristics of an entity about which the firm captures data. Record is a complete set of attributes for a single occurrence within an entity class. To find a particular record within the database, we must be able to identify it uniquely. 3. Describe and/ or differentiate the features of legacy system from a flat file structure. Flat file approach is most often associated with so called legacy systems. Eventually, modern database management systems will replace them, but in the meantime...
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