Oracle Database 19c: Data Warehousing Concepts — Lesson 3: ETL and ELT, Staging, Data Quality, Metadata, Lineage, and Orchestration

Learning Objectives

• Explain the architecture, workflow, or business purpose behind source profiling, extraction patterns, staging, transformations, and loading.
• Apply full, incremental, CDC awareness, dependencies, and restartability and quality dimensions, rules, exceptions, reconciliation, and stewardship in a controlled scenario.
• Validate outcomes and troubleshoot risks involving technical and business metadata, lineage, scheduling, monitoring, and evidence.

Detailed Topics

• source profiling, extraction patterns, staging, transformations, and loading
• full, incremental, CDC awareness, dependencies, and restartability
• quality dimensions, rules, exceptions, reconciliation, and stewardship
• technical and business metadata, lineage, scheduling, monitoring, and evidence

Instructor Demonstration

Demonstrate source profiling, extraction patterns, staging, transformations, and loading within an enterprise sales analytics warehouse defined from business questions through trusted dimensional delivery, then capture the exact configuration, command, transaction, report, model, query, code, or process evidence that proves the result for lesson 3.

Hands-On Exercise

Implement a controlled exercise covering full, incremental, CDC awareness, dependencies, and restartability and quality dimensions, rules, exceptions, reconciliation, and stewardship, then introduce and resolve an exception involving technical and business metadata, lineage, scheduling, monitoring, and evidence 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 source profiling, extraction patterns, staging, transformations, and loading, full, incremental, CDC awareness, dependencies, and restartability, quality dimensions, rules, exceptions, reconciliation, and stewardship, technical and business metadata, lineage, scheduling, monitoring, and evidence 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 ETL and ELT, Staging, Data Quality, Metadata, Lineage, and Orchestration in a realistic Oracle Database 19c: Data Warehousing Concepts scenario and validate the result with documented evidence.