Introduction

The Azure Analysis Services Deployment and Management course is designed to provide participants with the knowledge and skills required to implement, configure, and manage Azure Analysis Services (AAS). Azure Analysis Services is a cloud-based analytics service that enables businesses to build sophisticated data models and deliver insights at scale. This course covers everything from creating and deploying models to managing performance, security, and scalability within an Azure environment.

Prerequisites

• Basic understanding of Microsoft Azure and cloud computing
• Experience with data modeling and business intelligence tools
• Familiarity with SQL Server or Azure SQL Database
• Knowledge of data warehousing concepts
• Understanding of Power BI and other BI tools (optional)

Table of Contents

1. Introduction to Azure Analysis Services
   1.1 Overview of Azure Analysis Services
   1.2 Key Features and Benefits of AAS
   1.3 Use Cases for Azure Analysis Services
2. Setting Up Azure Analysis Services
   2.1 Creating and Configuring an Azure Analysis Services Instance
   2.2 Understanding Pricing Models and Sizing Options
   2.3 Exploring the Azure Portal for AAS
3. Data Modeling in Azure Analysis Services
   3.1 Designing Data Models with Tabular Models
   3.2 Using Power BI Desktop and Visual Studio for Development
   3.3 Importing Data and Creating Relationships(Ref: Comprehensive AZ-104: Microsoft Azure Admin Training)
4. Deploying Data Models to Azure Analysis Services
   4.1 Deploying Tabular Models from Power BI and Visual Studio
   4.2 Configuring Data Refresh and Scheduled Updates
   4.3 Managing Model Deployment with Azure DevOps
5. Securing Azure Analysis Services
   5.1 Configuring Authentication and Authorization
   5.2 Managing Role-Based Security in AAS Models
   5.3 Implementing Row-Level Security (RLS)
6. Managing Performance in Azure Analysis Services
   6.1 Optimizing Data Models for Query Performance
   6.2 Using Query Caching and Partitioning for Scalability
   6.3 Monitoring and Troubleshooting Performance
7. Scaling and High Availability in Azure Analysis Services
   7.1 Understanding AAS Scalability Options
   7.2 Configuring AAS for High Availability
   7.3 Using Geo-Replication for Global Performance
8. Monitoring and Maintaining Azure Analysis Services
   8.1 Monitoring AAS Health and Usage Metrics
   8.2 Configuring Alerts and Diagnostics
   8.3 Backup and Restore Strategies for AAS
9. Integrating Azure Analysis Services with Other Azure Services
   9.1 Connecting AAS with Azure Synapse Analytics
   9.2 Integrating with Power BI for Reporting and Dashboards
   9.3 Using AAS with Azure Logic Apps and Data Factory
10. Troubleshooting and Best Practices
    10.1 Common Issues in Azure Analysis Services
    10.2 Best Practices for Data Modeling and Management
    10.3 Ensuring Security and Compliance in AAS

Conclusion

Upon completion of this training, participants will have a strong understanding of how to deploy, manage, and optimize Azure Analysis Services for business intelligence solutions. With hands-on experience and advanced techniques, they will be equipped to handle real-world scenarios and scale their analytics platforms efficiently while ensuring security and high availability.

Reference