TOYOTA'S DATABASE SYSTEMS

Toyota's Database Systems

Toyota's Database Systems

Designing Toyota's database System

Toyota's database design is the task of "designing the structure of a Toyota's database in a given environment of users and applications such that all users' data requirements and all applications' process requirements is `best satisfied'. Toyota's database design is typically divided into four phases:

(1) requirements specification;

(2) conceptual design;

(3) logical design; and

(4) physical design.

The requirements specification phase is concerned with identifying the information needs of various users or groups. (Stefano, 1997) The conceptual design phase models the users' and applications' views of information and, possibly, includes a specification of the processing or use of the information. The objective of this phase is to produce a precise, formal representation of the requirements that is independent of any particular Toyota's database management system (DBMS) or approach. During the logical design phase, the conceptual scheme is translated into the logical data model of the selected DBMS; for example, a relational data model. (Sobiesiak, 2002) Finally, physical Toyota's database design transforms the logical data model design into a form that is suitable for the specific hardware and Toyota's database management system that are to be used.

Toyota's database design has often been described as an art rather than a science. Traditionally, it has been carried out on an ad hoc basis by a "Toyota's database design expert" who obtains information about a user's data needs through interviewing, examining existing documents and systems, and other such manual, labor-intensive means. The main weaknesses of this traditional approach are that Toyota's database designers are scarce, and the design of the Toyota's database is done by someone who is probably unfamiliar with the specific application domain.

Artificial intelligence technology may be able to help alleviate these problems. Given a set of requirements, system could generate a Toyota's database design automatically or semi-automatically. Such a system would incorporate the rules and heuristics used by human Toyota's database designers and apply them in a systematic way to each design task. The rule-based structure of many systems facilitates incremental modification and makes it possible for them to explain how a conclusion has been reached and the assumptions on which it is based. (Rebecca, 2005) This helps to develop user confidence in the system's recommendations.

Users also benefit from the computer's inexhaustible supply of patience. It never gets tired or bored asking the many repetitive questions required to elicit all of the attributes in a large Toyota's database design. It is possible, of course, that the user may become bored or impatient answering all these questions. From the developer's perspective, another advantage of this approach is that knowledge-based systems typically employ a modular, non-procedural structure. The objective of this article is to survey existing experimental knowledge-based systems for Toyota's database design in order to provide guidance for future research. The current state of the art is assessed by comparing and contrasting systems using a five-dimensional framework developed for that purpose. The next section of the article provides brief descriptions of a number ...