Azure Databricks for R-Based Data Analysis & Engineering — Lesson 3: Delta Lake, Pipelines and Reproducible Engineering

Learning Objectives

• Create Delta tables, medallion layers, incremental loads, merges, quality checks, versioning, and reliable pipeline steps
• Parameterize notebooks, schedule jobs, manage dependencies, capture logs, recover from failures, and document lineage
• Validate delta lake, pipelines and reproducible engineering decisions with documented requirements, evidence, risk controls, and measurable acceptance criteria

Detailed Topics

• Create Delta tables: Create Delta tables, medallion layers, incremental loads, merges, quality checks, versioning, and reliable pipeline steps
• Parameterize notebooks: Parameterize notebooks, schedule jobs, manage dependencies, capture logs, recover from failures, and document lineage
• Validate delta lake: Validate delta lake, pipelines and reproducible engineering decisions with documented requirements, evidence, risk controls, and measurable acceptance criteria

Guided Demonstration

1. Review the requirement, users, data, dependencies, permissions, risks, and expected result.
2. Demonstrate the relevant configuration, development, analysis, administration, testing, or operational workflow step by step.
3. Capture settings, outputs, logs, screenshots, calculations, test results, and other useful evidence.
4. Compare the observed result with acceptance criteria and explain any corrective action.

Hands-On Activity

Analyze a realistic business case, compare implementation options, and validate the selected approach.

• Document assumptions, prerequisites, and the planned sequence before starting.
• Complete the activity and preserve evidence of normal, boundary, and failure behavior.
• Record issues, corrective actions, reusable notes, and the next improvement priority.

Scenario Analysis

• Identify the business or technical decision that must be made.
• Compare valid implementation approaches and their trade-offs.
• Consider security, privacy, accessibility, performance, support, and operational impact.

Troubleshooting Focus

• Separate symptoms from causes and collect evidence before applying a fix.
• Check configuration, data, permissions, dependencies, capacity, connectivity, and recent changes.
• Validate rollback, recovery, ownership, user impact, and business continuity.

Validation Checklist

• The requirement, scope, inputs, and expected outcome are clear.
• The selected design or configuration is documented and follows approved standards.
• Normal, boundary, failure, security, accessibility, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply Delta Lake, Pipelines and Reproducible Engineering in a realistic scenario and validate the result with documented evidence.