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con rmations An audible error signal (see Fig 14-1) can be very helpful when visual-display terminals are used to enter large quantities of data An additional measure to catch errors is to report to the originator of the data the data values entered If, for instance, an order has been received by telephone or mail, the system can print a con rmation, in plain language, for inspection by the customer The purchaser then may realize that you are planning to deliver next week 501 adders instead of 50 ladders In many instances data are not entered directly into computer systems A common indirect entry method is the sequence of keypunching and veri cation (by rekeying and comparing), followed later by entry of a batch of data into the system Indirect data entry is often less costly and reduces dependence of system performance during data entry On the other hand, the detection of errors and feedback to the operators is deferred so that the cost of correction can be very high and repair of data frequently is omitted, knowingly or accidentally The decoupling of entry personnel from the computer system does avoid waste and frustration due to poor reliability and inconsistency of performance found in many systems Checking of data for consistency may be done only during periodic report generation Systems which do not provide feedback and incentives for error correction are doomed to eventual disuse Bad experiences by users, who attempt to obtain information from a database and receive obviously incorrect data, can easily cause rejection of positive aspects of automation as well In some situations the problem of improper action caused by poor data may be so serious that one should not allow an error correction to be made by an update of the record containing the error Instead a correction will be entered as a new record whose value will replace the previous value for a normal inquiry If a problem develops, we want to be able to go backward in time with a query of the form What was the value for x that the system would have provided at a time t and date d and retrieve the erroneous value then in use An example of this requirement can be found in the maintenance of medical records where errors in actions resulting from poor data can cause great harm and invite legal claims of malpractice A general solution to this problem is to routinely identify all data elements with a timestamp While this would in principle double the required storage space, the use of abbreviation techniques can reduce this factor The availability of a time identi er with every data element can also help in the processing and management of data Older data can be conveniently archived now, so that demands on highperformance storage devices may actually diminish
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Once correct data are entered into the system, we assume from the point of view of this chapter that they are safe The chapters on data security (11 to 13) will deal with this problem on a technical level
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The operation of a computer requires personnel and hardware We will concentrate in this chapter on the elements which relate to the load and performance factors that were developed in Sec 5-1 Broader issues are discussed in Chap 15 In order to simplify the procedure, we will use methods which can provide rough initial estimates of load on a given system These values can be re ned later when the system being designed has taken a more de nite form This section will concentrate on the storage-related equipment, whereas Sec 5-4 will discuss the processing-related system components 5-3-1 Storage Utilization When les undergo frequent and dynamic changes, not all the available le capacity can be utilized Depending on the le system used, considerably more space may be needed The density factor uD is used to adjust the expected storage cost throughout the design process The author has seen values for uD ranging from 90% (stable les in an environment which provided good space-allocation capability) to 25% (dynamic les in a structurally limited environment) A low value of uD does not necessarily imply an undesirable le design In les using direct access, for instance, available space will considerably enhance operational performance In addition, there will be wasted space W because of unspanned packing of records into blocks, which reduces the number of blocks needed for some records The total storage capacity required for the les making up a database is D=
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