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Requirements Gathering and Analysis
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The requirements-gathering stage is the first step in designing a new database. You must first find out, through an iterative process, the requirements of the organization for the database. The preliminary stage of the database life cycle addresses questions of this nature: Why is this new database necessary What objective is this database going to help achieve What current systems is the database going to replace What systems (if any) will the database have to interact with Who are the target users of the database This stage should yield a clear idea of the expectations of all concerned parties regarding the new system to be supported by the yet-to-be-created database. Requirements analysis for the firm involves extensive interviewing of users and management. The design team should also evaluate both the data that will go into the database and the expected output of the database. It s common practice to use graphical representations of the application systems to better understand the flow of data through the system. Data-flow diagrams (DFDs) or process models are commonly used at this stage to capture the data processes within and outside the application. Let s use an educational institution as an example to identify the processes. Say that a college has four processes: Manage Student Records, Manage Course Information, Manage Enrollment, and Manage Class Schedules. The Manage Student Records process maintains all student records, and it updates that information as necessary. The Manage Course Information process takes care of collecting all future course information from the various departments of the college. It is also responsible for making changes in the course list when departments add or drop courses for any reason.
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CHAPTER 2 RELA TION AL DA TA BAS E MODE LING AND DATA BASE DESIGN
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The Manage Enrollment process is more complex than others because it receives inputs from several processes. For example, when a student attempts to enroll in a new course, the Manage Enrollment process needs to first verify from the Manage Student Records process whether the student is in good standing. Next, it has to find out from the Manage Course Information process whether the course is indeed being offered. Then the Manage Enrollment process will enter this new student and course information in its part of the data flow. Only after the successful completion of all these processes can the Manage Class Schedules process send the new schedule out to the student. As complex as the brief description of data flows and business processes sounds, the use of sophisticated tools such as ERWin Data Modeler or PowerDesigner makes it easy to come up with fancy DFDs and process models with a minimum of frustration. You can find a list of data modeling tools, including all the popular ones as well as some free ones, at http://www.databaseanswers.com/ modelling_tools.htm.
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Logical Database Design
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Database design is both an art and a science. The science part comes in the form of adherence to certain rules and conditions, such as normalization (more about this later in the chapter). Database design is also an art, because you need to model relationships using your understanding of the realworld functioning of the organization. You can formally define logical database design as the process of creating a model of the real world for the database, independent of an actual database system or other physical considerations. Accuracy and completeness are the keys to this activity. One of the best things about this stage is that it s easy to take a draft design, throw it away, and start again, or simply amend it. It s a whole lot easier to tinker at the design stage than to deal with the production headaches of an already implemented database that isn t designed well. The logical design stage is sometimes broken up into a conceptual part and a logical part, but that s merely a distinction based on nomenclature. The conceptual database design is usually a precursor for the logical design phase and involves the modeling of the information without reference to any underlying data model. The logical design phase explicitly uses a specific data model, like the relational data model, for example you focus on the logical relationships involved in your conceptual design at this stage. Logical design involves conceptually modeling the database and ensuring that data in the tables passes integrity checks and isn t redundant. To satisfy these requirements, you need to implement data normalization principles, as you ll see shortly. Entity-relationship modeling (ER modeling) is a widely used methodology for logically representing and analyzing the components of the business system, and it is commonly used to model the enterprise after the requirements analysis is completed. The entity-relationship models are easy to construct, and their graphical emphasis makes them very easy to understand. However, you can t build a real-life RDBMS using the entity-relationship model of an enterprise. ER modeling s utility lies in designing databases, not implementing databases. ER modeling can t form the basis of a highlevel data-manipulation language like SQL, so the model that designers build using the ER modeling approach is translated to the relational model for implementation. By converting the abstract entityrelationship design into a relational database schema, the relational model helps convert the entityrelationship design into a relational DBMS.
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