Analysis within the Systems Development Life-Cycle: Book 2, Data Analysis—The Methods describes the methods for carrying out data analysis within the systems development life-cycle and demonstrates how the results of fact gathering can be used to produce and verify the analysis deliverables. A number of alternative methods of analysis other than normalization are suggested.
Comprised of seven chapters, this book shows the tasks to be carried out in the logical order of progression—preparation, collection, analysis of the existing system (which comprises the tasks of synthesis, verification, and approval)—and in each case how the input from the previous task is converted to the output for the next task until the final output—the verified approved deliverables—is obtained. The first chapter puts analysis into its place in the Systems Development Cycle (SDC) and explains what analysis really means. The next chapters cover, in logical sequence of dependency, the actual tasks of data analysis. The advantages and disadvantages of each method are described in the context of the life-cycle as a whole and in terms of the reliability of raw input, time problems, and so on. Each of the data models obtained using the different methods can be combined and subsequently refined using a number of step-by-step checks. The final chapter shows how the meta-model can be expanded by considering the intermediate outputs of the tasks of data analysis.
This text will be of interest to systems analysts and designers and those who are involved in expert systems.
Comprised of seven chapters, this book shows the tasks to be carried out in the logical order of progression—preparation, collection, analysis of the existing system (which comprises the tasks of synthesis, verification, and approval)—and in each case how the input from the previous task is converted to the output for the next task until the final output—the verified approved deliverables—is obtained. The first chapter puts analysis into its place in the Systems Development Cycle (SDC) and explains what analysis really means. The next chapters cover, in logical sequence of dependency, the actual tasks of data analysis. The advantages and disadvantages of each method are described in the context of the life-cycle as a whole and in terms of the reliability of raw input, time problems, and so on. Each of the data models obtained using the different methods can be combined and subsequently refined using a number of step-by-step checks. The final chapter shows how the meta-model can be expanded by considering the intermediate outputs of the tasks of data analysis.
This text will be of interest to systems analysts and designers and those who are involved in expert systems.
