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Systems Analysis and Design Lifecycle Overview

Learn the lifecycle concept, analysis, design, implementation, and maintenance of systems. Discover the PARIS model, role of Systems Analysis, and Requirements Analysis in successful system development. Dive into data-based and process-based systems analysis methods.

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Systems Analysis and Design Lifecycle Overview

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  1. LIS1510Library and Archives Automation IssuesSystems Analysis Andy Dawson School of Library, Archive & Information Studies, UCL(University of Malta 2008) Andy Dawson

  2. What we will be looking at today • The lifecycle concept • The need for good analysis • Describing the system • Identifying the needs • Practical exercise – process modelling

  3. The system life cycle (from yesterday) • Analysis • Design • Implementation • Evaluation • Decay • Replacement

  4. The systems development lifecycle • Strategic study • Feasibility study • Physical systems analysis • Logical systems definition • Logical systems design • Physical systems design • Implementation • Maintenance

  5. Or more simply • (Requirements) analysis • Design • Implementation • Maintenance

  6. The PARIS model • Plan • Ask • Record • Interpret • Specify

  7. As we said yesterday... • Why do so many systems seem to “fail”? • Misapprehension • Miscommunication • Misinterpretation • Misidentification • Misrepresentation

  8. The role of Systems Analysis • Systems analysis allows/helps us to: • identify systems • break them down • make them work (better) • Good systems analysis helps organisations to succeed • Necessary precursor to proper system selection

  9. Requirements Analysis • Identify elements • Model elements • Verify • Importance of Conceptual Modelling -Independence from physical implementation

  10. The focus of analysis • Systems tend to be Data-based or Process-based (transactional) • Transactions deal with transformations of data, input and output • Therefore we need to identify & develop transactions and data, and their interaction with the environment, to analyse a system

  11. How do we do this? • A process of expansion & contraction • Decomposition • Synthesis • Identifying and relating static & dynamic elements • Facts • Processes

  12. The value of models • Why do we model? • To improve clarity and accessibility • To show different relational aspects of the system • To help understanding • Different types of model • Data-based & Process-based • Varieties of model • Completeness of view

  13. Process modelling – The data flow diagram • Basic process modelling tool • full-scale analysis involves multiple models • different tools are used for data modelling etc • Top-down approach • Valuable for describing • current physical system • logical/desired system • Helps us to grasp system as a whole

  14. Key elements and considerations • Relationship to other models • Components • Sources/sinks (external entities) • Processes • Data stores • Data flows

  15. Symbology/notation • Importance of notation • Data flows between sources/sinks/stores via processes which transform the data • SSADM notation

  16. SSADM context diagram

  17. SSADM notation - first level DFD

  18. SSADM notation - second level DFD

  19. Naming • Importance of naming • Sources/sinks: generic descriptive • Stores: simple descriptive • Processes: “imperative action” concept • Flows: what is tranferred • Avoid ambiguity

  20. Hierarchies • Concept of levelling • Top-down decomposition • Practical levelling • Balancing • Ensure all inputs and outputs balance (match) across the levels of the hierarchy

  21. Referencing/numbering • Basic principles • Decimal heirarchies • Lower case lettering for entities • Mn/Dn stores • Stores within processes • Single/double flow lines and direction • Multiple sources/sinks/stores • Process locations/roles (physical)

  22. Constructing data flow diagrams • Follow the top-down approach • Define boundary (context diagram) • Identify • Static components • Key processes • Flows between them • Build -expand - refine - review

  23. Refining and developing the diagram • Iterative process! • Importance of • Balancing • Naming • Controlling complexity • Document flow diagrams • Data models

  24. After the break: A brief exercise in process modelling!

  25. That’s all for today! • Any questions? • Tomorrow: • Wrapping up the lifecycle • Feasibility studies and operational requirements • Systems selection and installation

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