Topics: Design, Completeness, Data modeling Pages: 2 (371 words) Published: March 15, 2008
SSADM Introduction

SSADM's approach to this problem is to provide a basis, the default Structural Model, plus some guidelines and a number of typical examples and expect this to be customized for each new project.
Generally, a SSADM customization strategy will be a component of a broader strategy which affects the way in which projects are undertaken. Documentation of the justification for customization is very important. SSADM is in the public domain, so no license fee has to be paid to use any part of it. SSADM suits both large and small projects. It fits each project's needs because it is scaleable and tailorable. It is designed to be customized. Whatever the size or type of application, only those elements which are useful to the project are used. If you tailor it to suit your needs, it will provide you with a method which is focused and effective. SSADM is rigorous. Not only does each technique have its own rules, but the method allows you to cross-check the quality and completeness of the deliverables of one technique against others within the method. It involves end-users throughout the analysis and design stage and provides quality criteria against which they can judge as SSADM deliverables.

SSADM avoids a user being locked in to a specific hardware or software environment. It separates the logical design from the physical implementation. This also means that a user can implement the solution on any number of different hardware and software environments without changing the logical design.

Many of the techniques used by SSADM are common to other structured methods, especially those used in the analysis phase. The main feature of SSADM's core techniques is their diagrammatic nature. Diagrams are capable of representing information quickly, in a compact form, and also relatively unambiguously.

The three major analysis techniques equate with the three SSADM views: Data Flow Modelling represents system processing; Logical Data Modelling...
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