Microsoft 365 - MCSA: Azure Database Development

Curriculum

40441A: Designing and Implementing Cloud Data Platform Solutions

Module 1: Microsoft Cloud Data Platform Overview

This module provides an overview of the Microsoft Data Platform Solutions in Hybrid and Cloud based scenarios. The module provides an overview of offerings and capabilities.

Lessons

• Microsoft Cloud Data Platform
• Microsoft SQL Server
• Common Tools
• Cloud Data Offerings
• Data Visualisations
• Cortana Analytics Suite

Module 2: Implement SQL Server on Azure VM

This module with a hands-on-lab describes the core capabilities of running SQL Server in a virtual machine environment (IAAS) on Azure.

Lessons

• Virtual machine components
• Storage Architecture
• Azure deployment models
• Virtual machine tiers
• Virtual machine deployments
• Deployment scenarios
• Move existing workloads
• Connecting to Azure VMs
• Domain joining VMs
• VM best practices

Lab : SQL Server in Azure VMs

Module 3: Implement SQL Database

This module with a hands-on-lab describes the core capabilities of implementing data platform solutions using SQL Database on Azure. The module provides details in service tiers and offerings.

Lessons

• What is SQL Database
• Data tiers/ Elastic data tiers
• Scalability Options
• Elastic Databases
• Elastic Database Tools
• SQL Database performance
• Service Tier Advisor

Lab : Implementing SQL Database

Module 4: SQL Database High Availability and disaster recovery

This module with a hands-on lab describes high availability and disaster recovery scenarios with SQL Database.

Lessons

• Business Continuity with SQL Database
• SQL Database HA/DR
• SQL Database Backup Solutions
• SQL Database Replication Scenarios

Lab : SQL Database HA/DR

Module 5: Hybrid HA/DR scenarios with SQL Server

This module with a hands-on lab exercise describes the design of high available, scalable data platform solutions on-premises, in the cloud and in hybrid cloud scenarios using SQL Server on premises and with Azure VMs.

Lessons

• HA/DR deployment architectures
• AlwaysOn availability groups
• AlwaysOn Failover Clustering
• Database Mirroring
• Log Shipping
• Backup to Azure
• Managed Backups
• SQL Server data files on Azure

Lab : Implement HA/DR with SQL Server in Azure VMs

Module 6: Design and Implement Security

This module with a hands-on-lab describes the security features and capabilities in SQL Server in Azure VMs and SQL Database including firewalls and auditing.

Lessons

• SQL Database Security Approach
• SQL Database Firewall Security
• SQL Database Active Directory Integration
• Encryption
• Row Level Security
• Dynamic Data Masking
• Auditing and Threat Detection

Lab : Design and Implement SQL Database Security

Module 7: Monitor and manage implementations on Azure

This module with a hands-on-lab focuses on management and deployment, monitoring for performance of SQL Database and SQL Server in Azure VMs.

Lessons

• Azure Automation Capabilities
• SQL Monitoring and Management
• Operational Insights

Lab : Monitoring and manage implementations

Module 8: Design and implement database solutions for SQL Server and SQL Database

This module covers design and architecture scenarios for implementation of database solutions using the Microsoft Cloud Data Platform. This module introduces key scenarios to discuss with classroom attendees in order to build out the right architecture and infrastructure based on architecture and business requirements.

Lessons

• Case Study - SQL Server Hybrid Scenario
• Case Study - Lift and Shift

20777A: Implementing Microsoft Azure Cosmos DB Solutions

Course Outline

Module 1: Introduction to Azure Cosmos DB

Describe the purpose and architecture of Cosmos DB.

Lessons

• Review of NoSQL database structures
• Migrating data and applications to Cosmos DB
• Managing data in Cosmos DB
• Lab : Creating and using a SQL API database in Cosmos DB
• Creating and configuring a Cosmos DB database
• Migrating data from a Mongo DB database to Cosmos DB
• Using the SQL API to access data
• Protecting data in a Cosmos DB database

After completing this module, students will be able to:

• Create and configure a Cosmos DB.
• Migrate data from a Mongo DB database to a Cosmos DB database.
• Describe accessing data using the SQL API.
• Describe how to protect data in a Cosmos DB.

Module 2: Designing and Implementing SQL API Database Applications

This module describes how to design documents and collections to meet business requirements, and how to use the SQL API to build applications that use these documents.

Lessons

• Document models in Cosmos DB
• Querying data in a SQL API database
• Querying and maintaining data programmatically
• Lab : Designing and implementing SQL API database applications
• Design the document structure & partitioning strategy for the product catalog for the retail system
• Importing product catalog data
• Querying product catalog information
• Maintaining stock levels in the product catalog

After completing this module, students will be able to:

• Design NoSQL document structures that support business requirements and enable efficient operations.
• Describe how to perform SQL queries against a SQL API database.
• Explain how to insert, modify, delete, and query data in a SQL API database programmatically.

Module 3: Implementing Server Side Operations

Describe how to create user-defined functions, stored procedures, and triggers.

Lessons

• Server-side programming with Cosmos DB
• Creating and using stored procedures
• Using triggers to maintain data integrity
• Lab : Writing user-defined functions, stored procedures and triggers
• Design and implement the document and collection structure
• Implement the shopping cart functionality in the online retail system.
• Extend the online retail system to create orders from the items in a shopping cart.
• Extend the online retail system further to enable customers to view orders and backorders.

After completing this module, students will be able to:

• Describe how Cosmos DB enables you to implement server-side operations by writing JavaScript code.
• Describe how use the JavaScript Query API to implement transactional operations with stored procedures.
• Describe how use create triggers that you can use to maintain integrity when inserting, updating, and deleting documents.

Module 4: Optimising and monitoring performance

Describe how to optimise a database, and how to monitor performance.

Lessons

• Optimising database performance
• Monitoring the performance of a database
• Lab : Tuning a database and monitoring performance
• Gathering execution statistics
• Examining how the different consistency models can impact throughput and latency
• Investigate the effects of triggers on performance
• Monitoring performance and tuning the partition key

After completing this module, students will be able to:

Describe how to tune the configuration of a database and collections for best performance.
Describe how to assess the performance of a document database and identify options for improving throughput.

Module 5: Designing and Implementing a Graph Database

This module describes how to create efficient graph database models using Cosmos DB.

Lessons

• Graph database models in Cosmos DB
• Designing Graph database models for efficient operation
• Lab : Designing and implementing a Graph database
• Implementing a recommendations engine for customers
• Recording product purchase information
• Query a Graph database to obtain analytics

After completing this module, students will be able to:

• Describe the features that Cosmos DB provides for implementing graph databases.
• Design NoSQL graph structures that support business requirements and enable efficient operations.

Module 6: Querying and Analysing Big Data with Cosmos DB

This module describes how to use Azure Search and HDInsight with Cosmos DB to query and analyse big data.

Lessons

• Integrating Cosmos DB with Azure search to optimise queries
• Analysing data in a Cosmos DB database using Apache Spark
• Visualising data in a Cosmos DB database
• Lab : Querying and Analysing Big Data with Cosmos DB
• Extending product search capabilities
• Performing end-of-month processing
• Visualising sales data
• Exploring sales data

At the end of this module, students will be able to:

• Describe how to integrate Cosmos DB with Azure Search to perform efficient query processing over big data.
• Describe how to analyse big data held in Cosmos DB using Apache Spark.
• Describe how to visualise data in Cosmos DB using Jupyter notebooks, Power BI, and Azure Databricks.

Module 7: Implementing Stream Processing with Cosmos DB

This module describes how to use Cosmos DB as a source and sink for streaming data.

Lessons

• Working with the Cosmos DB change feed
• Integrating Cosmos DB into streaming solutions
• Lab : Using Cosmos DB with stream processing
• Handling orders
• Maintaining stock analytic data
• Displaying rolling revenue for a given time period

After completing this module, students will be able to:

• Describe the Cosmos DB change feed, and how to use it to process data efficiently.
• Explain how to incorporate Cosmos DB into streaming solutions such as Apache Kafka, Apache Spark, and Azure Stream Analytics.