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Data Modeling Approach, Methods, and Techniques
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Designing appropriate data models is not a sinecure, and it is typically a task for IT specialists. On the other hand, it is almost impossible to design data models without the active participation of the future end users of the system. End users usually have the most expertise in their professional area, and they are also involved in the final system acceptance tests. Over the years, many methods have been developed to support the system development process itself, to generate system documentation, to communicate with project participants, and to manage projects to control time and costs. Traditional methods typically show a strict phasing of the development process and a description of what needs to be done in which order. That s why these methods are also referred to as waterfall methods. Roughly formulated, these methods distinguish the following four phases in the system development process:
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CHAPTER 1 RELATIONAL DATABASE SYSTEMS AND ORACLE
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1. Analysis: Describing the information needs and determining the information system boundaries 2. Logical design: Getting answers to the three questions about entities, attributes, and constraints, which were presented in the previous section 3. Physical design: Translating the logical design into a real database structure 4. Build phase: Building database applications Within the development methods, you can use various techniques to support your activities. For example, you can use diagram techniques to represent data models graphically. Some well-known examples of such diagram techniques are Entity Relationship Modeling (ERM) and Unified Modeling Language (UML). In the last section of this chapter, which introduces the sample tables used throughout this book, you will see an ERM diagram that corresponds with those tables. Another example of a well-known technique is normalization, which allows you to remove redundancy from a database design by following some strict rules. Prototyping is also a quite popular technique. Using prototyping, you produce quick and dirty pieces of functionality to simulate parts of a system, with the intention of evoking reactions from the end users. This might result in time-savings during the analysis phase of the development process, and more important, better-quality results, thus increasing the probability of system acceptance at the end of the development process. Rapid application development (RAD) is also a well-known term associated with data modeling. Instead of the waterfall approach described earlier, you employ an iterative approach. Some methods and techniques are supported by corresponding computer programs, which are referred to as computer-aided systems engineering (CASE) tools. For example, Oracle offers complete and integral support for system development, from analysis to system generation, with the Oracle Designer software.
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Semantics
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If you want to use information systems correctly, you must be aware of the semantics (the meaning of things) of the underlying data model. A careful choice for table names and column names is a good starting point, followed by applying those names as consistently as possible. For example, the attribute address can have many different meanings: home address, work address, mailing address, and so on. The meaning of attributes that might lead to this type of confusion can be stored explicitly in an additional semantic explanation to the data model. Although such a semantic explanation is not part of the formal data model itself, you can store it in a data dictionary a term explained in the next section.
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Information Systems Terms Review
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In this section, the following terms were introduced: Entities and attributes Generic versus specific Occurrences and attribute values
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CHAPTER 1 RELATIONAL DATABASE SYSTEMS AND ORACLE
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Base data and derivable data Redundancy and consistency Integrity and constraints Data modeling Methods and techniques Logical and physical design Normalization Prototyping and RAD CASE tools Semantics
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1.3 Database Management Systems
The preceding two sections defined the formal concept of an information system. You learned that if an organization decides to automate an information system, it typically uses some database technology. The term database can be defined as follows:
Definition A database is a set of data, needed to derive the desired information from an information
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