Implementing a Tabular Data Model by Using SQL Server Analysis Services — Lesson 1: Tabular Modeling Architecture and Data Preparation

Learning Objectives

• Explain tabular architecture, in-memory storage, compatibility levels, and model lifecycle
• Import and shape data from relational and supported analytical sources
• Design tables, relationships, data types, naming, and model structure for usability

Detailed Topics

• Explain tabular architecture: Explain tabular architecture, in-memory storage, compatibility levels, and model lifecycle
• Import and shape data from relational and supported analytical sources: Import and shape data from relational and supported analytical sources
• Design tables: Design tables, relationships, data types, naming, and model structure for usability

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

Create a model design from a reporting requirement and prepare the initial data structure.

• 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 Tabular Modeling Architecture and Data Preparation in a realistic scenario and validate the result with documented evidence.