Serverless ETL using OCI Data Integration — Lesson 2: Data Flows, Operators, Expressions, Parameters, Transformations, and Data Quality

Learning Objectives

• Assess the components, roles, data, dependencies, and expected outcome for data flows, operators, expressions, parameters, transformations, and data quality.
• Operate the required workflow with explicit checkpoints and exception handling.
• Resolve the result through data-flow previews, transformation output and explain any residual risk.

Detailed Topics

• Data Flows
• Operators
• Expressions
• Parameters
• Transformations
• Data Quality
• ownership, prerequisites, data, and acceptance criteria for data flows, operators, expressions, parameters, transformations, and data quality
• security, control, integration, performance, recovery, and support implications

Instructor Demonstration

Demonstrate data flows, operators, expressions, parameters, transformations, and data quality within a serverless ETL pipeline ingesting source data, applying governed transformations, loading a target, and recovering failed runs. Use representative data and capture data-flow previews, transformation output so another practitioner can verify the result.

Hands-On Exercise

Complete a controlled Serverless ETL using OCI Data Integration activity focused on data flows, operators, expressions, parameters, transformations, and data quality. Introduce a realistic case of schema drift, isolate its 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

• Identify who owns the decision, configuration, approval, and production support.
• Estimate how schema drift would affect users, data, service, or financial results.
• Define evidence for normal operation, a boundary condition, a failed case, and successful recovery.

Troubleshooting Guidance

When data flows, operators, expressions, parameters, transformations, and data quality does not produce the expected result, confirm scope, effective dates, identities, data context, dependencies, and recent changes. Review the most relevant data-flow previews, transformation output before editing configuration. Test one reversible hypothesis at a time, verify recovery, and confirm that the fix does not create schema drift elsewhere.

Validation Checklist

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

Lesson Outcome

Learners can apply Data Flows, Operators, Expressions, Parameters, Transformations, and Data Quality in a realistic Serverless ETL using OCI Data Integration situation and defend the result with course-specific evidence.