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Designing database systems

This excerpt, taken from Rebecca M. Riordan's book "Designing effective database systems," describes the processes involved in the analysis and design of database systems, starting with project life cycles.

This excerpt, taken from Rebecca M. Riordan's book "Designing effective database systems," describes the processes involved in the analysis and design of database systems, starting with project life cycles. You can download the entire chapter here.

Life cycle models

Once upon a time, systems analysts used a paradigm for the development process known as the waterfall model. There are several versions of this model.

The process begins with systems analysis, sometimes called requirements analysis, since it focuses on what the organization and the users require the system to do. Once the systems analysis has been completed and approved, the entire system is designed in detail. This phase is followed by planning and budgeting, and then the entire system is built, tested, and released. At least it is in theory.

The waterfall model is aesthetically pleasing. Each activity is completed and approved before the next one is begun, and the model allows a fine degree of control over budgets, staffing, and time. Deliver a waterfall project on time and on budget, and your clients will probably love you.

The problem, of course, is that reality is hardly ever this neat. The model assumes that all the information required to complete a task is avail-able during the performance of that task, and makes no allowance for new information coming to light later in the process. With the possible exception of very small systems (the sort of thing you can design and build for yourself over the course of a long weekend), this situation is unlikely in the extreme.


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 The waterfall model also doesn't allow for changes in business requirements during the course of the project. To assume that a system that met the business needs at the beginning of a project will still meet them at the end of a two- or three-year development process is foolhardy. Your clients will not love you for delivering a useless system, even if it is on time and on budget.

Understand, however, that the activities identified in the waterfall model are perfectly sound. In fact, omitting any of them from a development project is a recipe for disaster. The problem with the model is its linearity, its assumption that each phase need never be re-examined once it has been completed.

Several alternative life cycle models have been proposed to deal with the problems in the waterfall model. The spiral model assumes multiple iterations of the waterfall, each one expanding the scope of the previous iteration.

The problem with the spiral model is that, when strictly applied, the entire scope of the project is not considered until very late in the development project, and there is a (not insignificant) chance that later iterations will invalidate earlier work. This has always seemed to me a recipe for blown budgets and frustrated developers. The situation is particularly dangerous for database projects, where expansions in scope can change the semantics of the data, which requires a change to the database schema, and a change in the database schema can require unexpected -- and unpredictable -- changes throughout the system.

The model that I prefer for large systems, and use in my own work, is variously described as incremental development or evolutionary development.

In this model, which is in many ways simply a variation on the spiral model, the preliminary analysis is performed for the entire system, not just a portion of it. This is followed by an architectural design, again of the whole system. The goal of the architectural design is to define individual components that can be implemented more or less independently, and to describe the interactions and interdependencies between these components. The detailed design and implementation of each component is then performed using whichever model seems most appropriate. I use the spiral model for this phase because it allows greater flexibility in design and implementation.

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