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

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