Implementing a Tabular Data Model by Using SQL Server Analysis Services — Lesson 3: Security, Partitions, Processing, and Performance

Learning Objectives

• Configure roles, row-level security, perspectives, and user-facing metadata
• Design partitions, refresh, processing, storage, and deployment strategies
• Diagnose model size, calculation, relationship, and query-performance issues

Detailed Topics

• Configure roles: Configure roles, row-level security, perspectives, and user-facing metadata
• Design partitions: Design partitions, refresh, processing, storage, and deployment strategies
• Diagnose model size: Diagnose model size, calculation, relationship, and query-performance issues

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

Secure and tune a tabular model using a structured test and evidence checklist.

• 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 Security, Partitions, Processing, and Performance in a realistic scenario and validate the result with documented evidence.