Implementing a Tabular Data Model by Using SQL Server Analysis Services — Lesson 4: Deployment and Production Model Validation

Learning Objectives

• Deploy and manage tabular models across development and production environments
• Validate data accuracy, permissions, refresh, performance, and client-tool behavior
• Document support ownership, change control, recovery, and improvement actions

Detailed Topics

• Deploy and manage tabular models across development and production environments: Deploy and manage tabular models across development and production environments
• Validate data accuracy: Validate data accuracy, permissions, refresh, performance, and client-tool behavior
• Document support ownership: Document support ownership, change control, recovery, and improvement actions

Guided Demonstration

1. Review the requirement, environment, dependencies, roles, risks, and expected outcome.
2. Demonstrate the relevant configuration, analysis, code, or administration workflow step by step.
3. Capture settings, outputs, logs, screenshots, calculations, or test evidence.
4. Compare the observed result with the stated acceptance criteria.

Hands-On Activity

Complete a production-readiness review and produce a deployment and support plan.

• Document assumptions and the planned sequence before making changes.
• Complete the activity and preserve evidence of normal and exception behavior.
• Record issues, corrective actions, and reusable operational or development notes.

Troubleshooting Focus

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

Validation Checklist

• The requirement and expected outcome are clear.
• The selected configuration, design, query, code, or process is documented.
• Normal, boundary, failure, security, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply Deployment and Production Model Validation in a realistic scenario and validate the result with documented evidence.