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Analysis Within the Systems Development Life-Cycle
Book 2 Data Analysis — The Methods
1st Edition - January 1, 1987
Author: Rosemary Rock-Evans
9 7 8 - 1 - 4 8 3 1 - 4 0 8 1 - 0
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… Read more
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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.
PrefaceIntroductionAcknowledgmentsChapter 1 Introduction 1 Deliverables 2 The Task of Analysis The Nature of Systems Stages of Systems 3 SummaryChapter 2 Preparation 1 Definition of the Preparation Task The Inputs to Preparation The Outputs of the Preparation Task 2 Establish Which Areas Come within the Scope Identify the Designed System Identify the Real Worlds Available 3 Identify and Record Sources Available Users/Jobs/People Documentation Available Analysts/Designers 4 Decide on Best Source for Area of Input Required 5 Decide on Method of Collection Interview Phone Call Meeting Teleconferencing Questionnaire Co-option Observation Participation Collection as Appropriate Collection Systems Unstructured Data 6 SummaryChapter 3 Collection 1 Introduction 2 Plan Collection Sessions Identify the Planned Sessions Required Decide Sampling to be Used Identify Actual Sessions Required Select Sessions Based on Time Constraints Sequence 3 Arrange Collection Session Obtain Permission to Hold Decide on Participants Decide Location Decide Times and Dates Produce List of Topics Produce Agenda/Questionnaire Confirm Collection Session Decide Method of Fact Recording Other Tasks 4 Hold Collection Session Collecting questionnaires Interviewing/Phone Call Holding a Meeting or Teleconference The Observation/Experimentation Process Participation Collection of Documentation Co-Option 5 Validate Raw Input 6 SummaryChapter 4 Synthesis 1 Introduction 2 Convert Data to Deliverable Form Convert Real World Data Convert Design Abstraction Deliverables to Analysis Deliverables Convert Design Occurrences Summary 3 Match and Compare Models to Produce one Comprehensive Model 4 Refine the Result Generalize the Entity Types Search for Synonymous Entity Types Generalize Model over Time Remove Redundant Relationship Types Expand Many-to-Many Relationship Types Investigate One-to-One Relationship Types Generalize Attribute Types Ensure That Every Part of the Attribute Type Name is Essential to Its Definition Ensure That No Artificial 'Moves' of Attribute Values Occur Remove Entity Types Which Have No Attribute Types Other than Their Identifier Remove 'Embedded' Relationship Types Remove 'Repeating Groups' of Attribute Types Remove Artificial Dependencies between Attribute Types Remove Duplicated Attribute Types Check That the Attribute Types and Entity Types Give a Stable and Historical Representation of the Real World Check That Every Permitted Value Can Be Described by an Attribute Type 5 SummaryChapter 5 Verification 1 Introduction 2 Verification That the Model is a True Representation of the Real World Double Sourcing Duplicate Sourcing Different Sample 3 Verification That the Model is Complete, Logically Sound and Consistent Duplicate Synthesis Quality Control Joint Walkthrough 4 SummaryChapter 6 Approval 1 Introduction Definition Objective/Purpose Who Gives Approval? 2 The Process of Approval Decide Method of Approval Produce Report Conduct User Approval Session Obtaining Approval/Sign off 3 SummaryChapter 7 Summary 1 Introduction 2 The Main Activities Covered in this Book The Effect on the Meta-model and the Deliverables of Data Analysis 3 Your General questions Answered Documentation—Forms or a Data Dictionary? What Can Go Wrong/What Must be Prepared for? How to Get Started?Glossary and AcronymsIndex