Oracle AI Database: SQL Workshop Live Class — Lesson 2: Single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING

Learning Objectives

• Explain how single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING changes the end-to-end technical or business process.
• Configure single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING with explicit inputs, controls, outputs, exceptions, and rollback points.
• Prove the implementation using join and aggregation reconciliation and document unresolved risk.

Detailed Topics

• Single-row functions
• conversion functions
• conditional expressions
• aggregates
• GROUP BY
• HAVING
• Ownership, prerequisites, data, and acceptance criteria for single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING
• Security, control, integration, performance, recovery, compliance, and support implications

Instructor Demonstration

Demonstrate single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING within a learner building reliable Oracle SQL queries and data-change operations that produce correct, explainable, and controlled results. Use representative data and capture join and aggregation reconciliation so another practitioner can reproduce and verify the result.

Hands-On Exercise

Complete a controlled activity focused on single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING. Introduce a realistic case of join duplicates distort results, isolate the cause, apply a reversible correction, and rerun the acceptance checks.

1. Record the requirement, environment, identities, dependencies, data, controls, and expected result.
2. Perform the workflow and capture course-specific evidence before and after each material change.
3. Test normal, boundary, failure, security, reconciliation, recovery, and operational conditions.
4. Document the root cause, correction, rollback, owner, support action, and next improvement priority.

Scenario Analysis

• Map the process from initiating condition through each transformation to the final output.
• Locate the control point most likely to prevent or expose join duplicates distort results.
• Recommend monitoring, escalation, and operational handover requirements.

Troubleshooting Guidance

When single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING does not produce the expected result, confirm scope, effective dates, identities, data context, dependencies, and recent changes. Review join and aggregation reconciliation before modifying configuration or data. Test one reversible hypothesis at a time, verify recovery, and confirm that the fix does not create a new control, security, performance, compliance, or integration defect.

Validation Checklist

• Prerequisites, ownership, data context, settings, and expected outcomes are documented.
• The result is reproducible and supported by join and aggregation reconciliation.
• Security, controls, data quality, integration, performance, recovery, compliance, and support conditions are reviewed.
• Exceptions, corrective action, rollback, approvals, monitoring, and handover are recorded.

Lesson Outcome

Learners can apply Single-row functions, conversion functions, conditional expressions, aggregates, GROUP BY, HAVING in a realistic Oracle AI Database: SQL Workshop Live Class situation and defend the result with course-specific evidence.