Lesson 2: Sources, Sinks, Schemas, Pipelines, Expressions, Transformations, and Data Quality

Lesson Overview

This lesson develops practical capability in sources, sinks, schemas, pipelines, expressions, transformations, and data quality for the Implementing Splunk Data Stream Processor 1.2 Training. Learners connect the topic to the wider course goal of planning streaming data pipelines, transformations, routing, observability, and operational controls.

Topics Covered

Sources, Sinks, Schemas, Pipelines, Expressions, Transformations, and Data Quality: purpose, terminology, architecture, roles, and expected business or operational outcomes
Core Splunk data, searches, configuration, objects, integrations, interfaces, and security controls relevant to the topic
Design decisions, dependencies, risks, permissions, performance considerations, and governance requirements
Guided practice focused on configuration, searches, integrations, security controls, and implementation patterns
Testing, validation, diagnostics, troubleshooting, documentation, and operational support

Practical Activity

Build or configure the core searches, objects, settings, integrations, or workflows covered in the lesson and record expected results.
Capture assumptions, configuration choices, expected results, test evidence, and remediation notes in a reusable worksheet.
Review the completed exercise against security, data quality, performance, maintainability, and support-readiness criteria.

Key Takeaways

Explain the purpose and architecture of sources, sinks, schemas, pipelines, expressions, transformations, and data quality.
Apply the principal Splunk features and workflows required for the lesson scenario.
Validate results, identify common failure points, document decisions, and support a controlled operational outcome.

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Implementing Splunk Data Stream Processor 1.2 Training 1 Section4 Lessons32 Hours

Curriculum