Data Modelling and Design — Lesson 2: Logical Models, Attributes, Keys, Normalization, and Business Rules

Learning Objectives

• Explain the architecture, workflow, or business purpose behind entities, attributes, domains, optionality, and logical identifiers.
• Apply candidate, primary, alternate, and foreign keys and functional dependencies and first, second, and third normal forms in a controlled scenario.
• Validate outcomes and troubleshoot risks involving associative entities, subtype structures, constraints, and rule traceability.

Detailed Topics

• entities, attributes, domains, optionality, and logical identifiers
• candidate, primary, alternate, and foreign keys
• functional dependencies and first, second, and third normal forms
• associative entities, subtype structures, constraints, and rule traceability

Instructor Demonstration

Demonstrate entities, attributes, domains, optionality, and logical identifiers within a customer-and-order platform redesigned to eliminate ambiguity, duplication, inconsistent keys, and reporting gaps, then capture the exact configuration, command, transaction, report, model, query, code, or process evidence that proves the result for lesson 2.

Hands-On Exercise

Implement a controlled exercise covering candidate, primary, alternate, and foreign keys and functional dependencies and first, second, and third normal forms, then introduce and resolve an exception involving associative entities, subtype structures, constraints, and rule traceability while preserving before-and-after evidence.

1. Confirm the environment, identities, inputs, dependencies, risks, and expected outcome.
2. Complete the course-specific configuration, development, analysis, or process workflow.
3. Capture settings, commands, data, outputs, logs, reports, screenshots, calculations, or test results.
4. Compare the observed result with acceptance criteria and document corrective action.

Scenario Analysis

• Identify the technical or business decision that must be made.
• Compare valid approaches and their security, performance, reliability, cost, compliance, and support trade-offs.
• Define rollback, recovery, ownership, communication, and evidence requirements.

Troubleshooting Guidance

Diagnose issues across entities, attributes, domains, optionality, and logical identifiers, candidate, primary, alternate, and foreign keys, functional dependencies and first, second, and third normal forms, associative entities, subtype structures, constraints, and rule traceability without making an unverified production change. Separate symptoms from causes, gather evidence, test the smallest reversible correction, rerun validation, and record preventive action.

Validation Checklist

• The requirement, scope, inputs, dependencies, and expected result are documented.
• The result is reproducible and supported by course-specific evidence.
• Normal, boundary, failure, security, performance, and operational conditions are reviewed.
• Exceptions, rollback, ownership, and the next improvement priority are recorded.

Lesson Outcome

Learners can apply Logical Models, Attributes, Keys, Normalization, and Business Rules in a realistic Data Modelling and Design scenario and validate the result with documented evidence.