Order the standard stages of data/system design from understanding needs to deployment. 1. Implementation 2. Conceptual Modelling 3. Requirements Analysis 4. Logical Modelling 5. Physical Model 6. Schema Refinement
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A3, 2, 1, 4, 6, 5
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B3, 2, 4, 6, 5, 1
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C1, 3, 2, 6, 5, 4
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D3, 2, 5, 4, 6, 1
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E2, 3, 4, 6, 1, 5
Answer
Correct Answer: 3, 2, 4, 6, 5, 1
Explanation
Introduction / Context:This question examines knowledge of a widely used pipeline for data/system design: requirements → conceptual → logical → refinement → physical → implementation.
Given Data / Assumptions:
- We seek a coherent end-to-end order for building a data system.
- Refinement happens after logical modelling to normalize and optimize the schema.
- Physical model precedes actual implementation.
Concept / Approach:Capture user needs first; translate needs into technology-agnostic concepts; map concepts to a logical schema; refine (e.g., normalization); map to physical specifics (indexes, partitions); finally implement/deploy.
Step-by-Step Solution:3 Requirements Analysis → understand problems and constraints.2 Conceptual Modelling → entities/relationships independent of DBMS.4 Logical Modelling → tables/keys at DBMS-agnostic level.6 Schema Refinement → remove anomalies, optimize.5 Physical Model → storage/indexing choices on a chosen DBMS.1 Implementation → build, load, and deploy.
Verification / Alternative check:Implementation must be last; requirements must be first. Refinement logically follows an initial logical design.
Why Other Options Are Wrong:Options starting with implementation are backwards; placing physical before logical or refinement breaks dependencies.
Common Pitfalls:Confusing conceptual vs logical; skipping refinement leads to update anomalies.
Final Answer:3, 2, 4, 6, 5, 1