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The database development process does not exist in isolation Database development is conducted along with activities in the systems analysis, systems design, and systems implementation phases The conceptual data modeling phase is performed as part of the sys tems analysis phase The logical database design phase is performed during systems design The distributed database design and physical database design phases are usually divided between systems design and systems implementation Most of the preliminary decisions for the last two phases can be made in systems design However, many physical design and distributed design decisions must be tested on a populated database Thus, some activities in the last two phases occur in systems implementation To fulfill the goals of database development, the database development process must be tightly integrated with other parts of information systems development To produce data, process, and interaction models that are consistent and complete, cross-checking can be performed, as depicted in Figure 27 The information systems development process can be split between database development and applications development The database devel opment process produces ERDs, table designs, and so on as described in this section The applications development process produces process models, interaction models, and proto types Prototypes are especially important for cross-checking A database has no value unless it supports intended applications such as forms and reports Prototypes can help re veal mismatches between the database and applications using the database

Measures of system utilization that can be pro tably monitored in-

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As a database designer, you need two different kinds of skills as depicted in Figure 28 The conceptual data modeling and logical database design phases involve mostly soft skills Soft skills are qualitative, subjective, and people-oriented Qualitative skills emphasize the generation of feasible alternatives rather than the best alternatives As a database designer, you want to generate a range of feasible alternatives The choice among feasible alterna tives can be subjective You should note the assumptions in which each feasible alternative

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Statistics of device utilization The percentage activity times of processors, channels, controllers, and disks It is desirable to have both average values as well as values which pertain to the busy periods of system operation Statistics of le utilization A matrix of user process versus le activities is the basic measure The relative ratios of type of access such as fetch, get next, and update are important for decisions about the le organization File density (space used versus space allocated) is another measure Statistics of record utilization The frequency with which records are accessed for read or update provides a measure which can be used to provide optimization in systems where records are chained The dates and times of last access and update are important for the maintenance of integrity, as is the identi cation of the process which updated the records Statistics of attribute utilization The frequency with which attribute values are requested, updated, used as keys, or used as further search arguments provides the data for optimal tuple membership selection

template <class ForIter, class T, class Comp> bool binary_search(ForIter start, ForIter end, const T &val, Comp cmpfn);

The measures can be obtained by continuous monitoring or by selective sampling The best repository for data obtained from monitoring depends on the system design It can be di cult to bring all the measurements together for automated analysis A regular logging tape provides the most obvious repository

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Data on device utilization may be provided by the operating system File utilization data can be saved in a le directory when a le is closed Record activity logging was essential for comprehensive backup, but many systems do not provide this service Data on record activity can be collected with the record when records are written or updated,

The binary_search( ) algorithm performs a binary search on an ordered sequence beginning at start and ending with end for the value specified by val It returns true if val is found and false otherwise The first version compares the elements in the specified sequence for equality The second version allows you to specify your own comparison function

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but the cost of rewriting a record which has been read in order to collect access monitoring data is excessive Attribute activity can be recorded with the schema, and recorded when the associated le is closed or when a process terminates

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