Structured system analysis is a systematic approach to understanding and defining a system's requirements, functions, and processes. It uses a structured methodology to break down complex systems into smaller, manageable components, making it easier to analyze and understand.
Key Characteristics of Structured System Analysis:
- Top-Down Approach: Starts with a high-level overview of the system and gradually drills down to the details.
- Data Flow Diagrams (DFDs): Visual representations of data flow within a system.
- Structured English: A precise and unambiguous way to describe system processes using a limited set of keywords and syntax.
- Decision Tables: Tables that represent complex decision-making logic in a structured format.
- Data Dictionaries: Centralized repositories of data definitions, attributes, and relationships.
- Modular Design: Breaking down the system into smaller, independent modules, making it easier to maintain and modify.
Benefits of Structured System Analysis:
- Improved Communication: Provides a common language and framework for stakeholders to communicate effectively.
- Clearer Requirements: Helps in defining and documenting system requirements more precisely.
- Reduced Errors: Structured approach minimizes the risk of errors and inconsistencies.
- Easier Maintenance: Modular design facilitates easier maintenance and modifications.
- Increased Efficiency: Streamlines the system development process, leading to faster development times.
Examples of Structured System Analysis in Action:
- Developing a new software application: Analyzing user requirements, designing system architecture, and defining data structures using DFDs, structured English, and decision tables.
- Improving a business process: Mapping out the current process flow, identifying bottlenecks, and proposing improvements using DFDs and structured English.
- Designing a new database: Defining data entities, attributes, and relationships using data dictionaries.
Structured system analysis provides a robust framework for understanding and defining complex systems, ensuring clarity, efficiency, and accuracy in system development and maintenance.
