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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.
Chapter 1 Introduction
2 The Task of Analysis
The Nature of Systems
Stages of Systems
Chapter 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
4 Decide on Best Source for Area of Input Required
5 Decide on Method of Collection
Collection as Appropriate
Chapter 3 Collection
2 Plan Collection Sessions
Identify the Planned Sessions Required
Decide Sampling to be Used
Identify Actual Sessions Required
Select Sessions Based on Time Constraints
3 Arrange Collection Session
Obtain Permission to Hold
Decide on Participants
Decide Times and Dates
Produce List of Topics
Confirm Collection Session
Decide Method of Fact Recording
4 Hold Collection Session
Holding a Meeting or Teleconference
The Observation/Experimentation Process
Collection of Documentation
5 Validate Raw Input
Chapter 4 Synthesis
2 Convert Data to Deliverable Form
Convert Real World Data
Convert Design Abstraction Deliverables to Analysis Deliverables
Convert Design Occurrences
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
Chapter 5 Verification
2 Verification That the Model is a True Representation of the Real World
3 Verification That the Model is Complete, Logically Sound and Consistent
Chapter 6 Approval
Who Gives Approval?
2 The Process of Approval
Decide Method of Approval
Conduct User Approval Session
Obtaining Approval/Sign off
Chapter 7 Summary
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 Acronyms
- No. of pages:
- © Pergamon 1987
- 1st January 1987
- eBook ISBN:
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