Systems Analysis and Design Overview

Systems Analysis and Design

• Systems Analysis: A thorough examination of existing processes to identify inefficiencies and define improvements; determining what a system should do to meet user needs.
• Key Steps in Systems Analysis: Information gathering (interviews, observations, document analysis), requirement analysis (defining functional and non-functional needs), and creating documentation (detailed specifications).
• Example: Analyzing an inventory management system in a retail store to identify bottlenecks and optimize stock control.
• System Design: Creating detailed specifications on how the components of a system will interact to meet the requirements defined in analysis. Involves architectural design and interface design.
• Key Steps in System Design: Logical design (system functions without technology constraints), physical design (implementation details using specific hardware and software), detailing database schemas.
• Example: Designing a relational database schema for a system that handles customer orders and integrates with online payment.
• System Development Life Cycle (SDLC): A framework for planning, creating, testing, and deploying an information system.
• SDLC Phases: Planning (defining project objectives), Analysis (gathering detailed user needs), Design (system architecture and interfaces), Implementation (coding and rigorous testing), Support and Maintenance (updates and troubleshooting).

Visual Representations

• Data Flow Diagrams (DFDs): Depict data flow through a system, showing processes, data stores, and external entities.
• DFD Types: Context diagram (highest level overview), level 1 DFD (further breakdown of main processes).
• Symbols: Processes (actions), data flows (movement), data stores (data storage), and external entities (inputs/outputs).
• Example DFD: Shows data flow between customer, order processing, and inventory systems.
• Use Case Diagrams: Illustrate interactions between users (actors) and the system.
• Components: Actors (users), use cases (functional tasks), relationships (communication between actors and use cases).
• Entity-Relationship Diagrams (ERDs): Represent data entities, attributes, and relationships.
• Components: Entities (objects/data), Attributes (characteristics of data), Relationships (connections between entities).

Types of Information Systems

• Transaction Processing Systems (TPS): Manage daily transactions. Example: retail checkout system.
• Management Information Systems (MIS): Reports based on TPS data for planning/decision-making. Example: weekly sales reports.
• Decision Support Systems (DSS): Supports decision-making by analyzing data and providing predictive insights. Example: financial modeling software.
• Enterprise Resource Planning (ERP): Unified core business processes across departments. Example: SAP, Oracle ERP.

Development Approaches

• Agile Methodologies: Flexible and iterative approach to development emphasizing collaboration and responsiveness.
• Agile Practices: Scrum (sprints, tasks, roles), Kanban (visual workflow management).
• Iterative Development: Building a system incrementally with each iteration refining features based on user feedback.
• Early Issue Detection: Early feedback allows for earlier identification of problems.
• Feedback Integration: Incorporating user suggestions enhances product relevant.

Advanced Diagrams and Tools

• System Sequence Diagrams (SSDs): Visualize sequence of operations between actors and system. Use lifelines and messages to track interactions.
• UML Class Diagrams: Represent class structure in a system including attributes and methods. Show class components (name, attributes, operations) and associations between classes.
• Work Breakdown Structure (WBS): Hierarchical representation of project tasks; organizes and assigns responsibilities. Includes phases (analysis, design, etc.), tasks, and relationships.

Project Management

• Detailed Work Breakdown Structure (WBS): Breaks down projects into smaller and more manageable components. This increases clarity, resource management, and scheduling.
• Techniques: Decomposition, task numbering.
• Risk Management Strategies: Systematic identification, analysis, and response to project risks. Example: Technical risks, Schedule risks.
• Comprehensive Cost-Benefit Analysis: Comparing project costs to anticipated benefits using metrics like Net Present Value (NPV) and Return on Investment (ROI).
• Common Reasons for Project Failure: Incomplete requirements, unclear direction; solutions include clear documentation and stakeholder involvement.
• Best Practices for Success: Clear documentation, regular stakeholder involvement.