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1.1 Information Needs and Information Systems
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Organizations have business objectives. In order to realize those business objectives, many decisions must be made on a daily basis. Typically, a lot of information is needed to make the right decisions; however, this information is not always available in the appropriate format. Therefore, organizations need formal systems that will allow them to produce the required information, in the right format, at the right time. Such systems are called information systems. An information system is a simplified reflection (a model) of the real world within the organization. Information systems don t necessarily need to be automated the data might reside in card files, cabinets, or other physical storage mechanisms. This data can be converted into the desired information using certain procedures or actions. In general, there are two main reasons to automate information systems: Complexity: The data structures or the data processing procedures become too complicated. Volume: The volume of the data to be administered becomes too large.
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If an organization decides to automate an information system because of complexity or volume (or both), it typically will need to use some database technology. The main advantages of using database technology are the following: Accessibility: Ad hoc data-retrieval functionality, data-entry and data-reporting facilities, and concurrency handling in a multiuser environment Availability: Recovery facilities in case of system crashes and human errors Security: Data access control, privileges, and auditing Manageability: Utilities to efficiently manage large volumes of data
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When specifying or modeling information needs, it is a good idea to maintain a clear separation between information and application. In other words, we separate the following two aspects: What: The information content needed. This is the logical level. How: The desired format of the information, the way that the results can be derived from the data stored in the information system, the minimum performance requirements, and so on. This is the physical level.
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Database systems such as Oracle enable us to maintain this separation between the what and the how aspects, allowing us to concentrate on the first one. This is because their implementation is based on the relational model. The relational model is explained later in this chapter, in Sections 1.4 through 1.7.
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1.2 Database Design
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One of the problems with using traditional third-generation programming languages (such as COBOL, Pascal, Fortran, and C) is the ongoing maintenance of existing code, because these languages don t separate the what and the how aspects of information needs. That s why programmers using those languages sometimes spend more than 75% of their precious time on maintenance of existing programs, leaving little time for them to build new programs. When using database technology, organizations usually need many database applications to process the data residing in the database. These database applications are typically developed using fourth- or fifth-generation application development environments, which significantly enhance productivity by enabling users to develop database applications faster while producing applications with lower maintenance costs. However, in order to be successful using these fourth- and fifth-generation application development tools, developers must start thinking about the structure of their data first. It is very important to spend enough time on designing the data model before you start coding your applications. Data model mistakes discovered in a later stage, when the system is already in production, are very difficult and expensive to fix.
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Entities and Attributes
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In a database, we store facts about certain objects. In database jargon, such objects are commonly referred to as entities. For each entity, we are typically interested in a set of observable and relevant properties, commonly referred to as attributes.
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When designing a data model for your information system, you begin with two questions: 1. 2. Which entities are relevant for the information system Which attributes are relevant for each entity, and which values are allowed for those attributes
We ll add a third question to this list before the end of this chapter, to make the list complete. For example, consider a company in the information technology training business. Examples of relevant entities for the information system of this company could be course attendee, classroom, instructor, registration, confirmation, invoice, course, and so on. An example of a partial list of relevant attributes for the entity ATTENDEE could be the following: Registration number Name Address City Date of birth Blood group Age Gender
For the COURSE entity, the attribute list could look as follows: Title Duration (in days) Price Frequency Maximum number of attendees
Note There are many different terminology conventions for entities and attributes, such as objects, object types, types, object occurrences, and so on. The terminology itself is not important, but once you have made a choice, you should use it consistently.
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