MOC 20777 - Implementing Microsoft Azure Infrastructure Solutions

This three-day Implementing Microsoft Azure Infrastructure Solutions training class is aimed at database professionals who are looking to implement a Cosmos DB solution.
The primary audience for this course is database developers and architects (IT professionals, developers, and information workers) who plan to implement big data solutions on Azure using Cosmos DB.

  Microsoft Certified Partner

Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Goals
  1. Learn to describe the purpose and architecture of Azure Cosmos DB.
  2. Learn to describe how to design documents and collections to meet business requirements, and how to use the SQL API to build applications that use these documents.
  3. Learn to describe how to create user-defined functions, stored procedures, and triggers.
  4. Learn to describe how to tune a database, and how to monitor performance.
  5. Learn to describe how to create efficient Graph database models using Cosmos DB.
  6. Learn to describe how to use Azure Search, HDInsight, Azure Databricks, and Power BI with Cosmos DB to query and analyze big data.
  7. Learn to describe how to use Cosmos DB as a source and sink for streaming data.
Outline
  1. Introduction to Azure Cosmos DBDescribe the purpose and architecture of Cosmos DB. Lessons
    1. Review of NoSQL database structures
    2. Migrating data and applications to Cosmos DB
    3. Managing data in Cosmos DB
    4. Lab: Creating and using a SQL API database in Cosmos DB
      1. Creating and configuring a Cosmos DB database
      2. Migrating data from a Mongo DB database to Cosmos DB
      3. Using the SQL API to access data
      4. Protecting data in a Cosmos DB database
  2. Designing and Implementing SQL API Database Applications
    1. Document models in Cosmos DB
    2. Querying data in a SQL API database
    3. Querying and maintaining data programmatically
    4. Lab: Designing and implementing SQL API database applications
      1. Design the document structure & partitioning strategy for the product catalog for the retail system
      2. Importing product catalog data
      3. Querying product catalog information
      4. Maintaining stock levels in the product catalog
  3. Implementing Server Side OperationsDescribe how to create user-defined functions, stored procedures, and triggers.Lessons
    1. Server-side programming with Cosmos DB
    2. Creating and using stored procedures
    3. Using triggers to maintain data integrity
    4. Lab: Writing user-defined functions, stored procedures and triggers
      1. Design and implement the document and collection structure
      2. Implement the shopping cart functionality in the online retail system.
      3. Extend the online retail system to create orders from the items in a shopping cart.
      4. Extend the online retail system further to enable customers to view orders and backorders.
  4. Optimizing and monitoring performanceDescribe how to optimize a database, and how to monitor performance.Lessons
    1. Optimizing database performance
    2. Monitoring the performance of a database
    3. Lab: Tuning a database and monitoring performance
      1. Gathering execution statistics
      2. Examining how the different consistency models can impact throughput and latency
      3. Investigate the effects of triggers on performance
      4. Monitoring performance and tuning the partition key
  5. Designing and Implementing a Graph Database
    1. Graph database models in Cosmos DB
    2. Designing Graph database models for efficient operation
    3. Lab: Designing and implementing a Graph database
      1. Implementing a recommendations engine for customers
      2. Recording product purchase information
      3. Query a Graph database to obtain analytics
  6. Querying and Analyzing Big Data with Cosmos DB
    1. Integrating Cosmos DB with Azure search to optimize queries
    2. Analyzing data in a Cosmos DB database using Apache Spark
    3. Visualizing data in a Cosmos DB database
    4. Lab: Querying and Analyzing Big Data with Cosmos DB
      1. Extending product search capabilities
      2. Performing end-of-month processing
      3. Visualizing sales data
      4. Exploring sales data
      5. At the end of this module, students will be able to:
      6. Describe how to integrate Cosmos DB with Azure Search to perform efficient query processing over big data.
      7. Describe how to analyze big data held in Cosmos DB using Apache Spark.
      8. Describe how to visualize data in Cosmos DB using Jupyter notebooks, Power BI, and Azure Databricks.
  7. Implementing Stream Processing with Cosmos DB
    1. Working with the Cosmos DB change feed
    2. Integrating Cosmos DB into streaming solutions
    3. Lab: Using Cosmos DB with stream processing
      1. Handling orders
      2. Maintaining stock analytic data
      3. Displaying rolling revenue for a given time period
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this Azure class:

  • The fundamental concepts of partitioning, replication, and resource governance for building and configuring scalable applications that are agnostic of a Cosmos DB API.
  • A basic working knowledge of the Cosmos DB SQL API.
Preparing for Class

Training for your Team

Length: 3 Days
  • Private Class for your Team
  • Online or On-location
  • Customizable
  • Expert Instructors

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