Course Outline Module 1: Introduction to Azure Cosmos DB

• 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 Cosmos DB.

• Migrate data from a Mongo DB database to a Cosmos DB database.

• Describes accessing data using the SQL API.

• Describes how to protect data in a Cosmos DB.

• 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.

• Describes 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 Describes 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.

• Describes how to use the JavaScript Query API to implement transactional operations with stored procedures.

• Describes how to use create triggers that you can use to maintain integrity when inserting, updating, and deleting documents.

Module 4: Optimizing and monitoring performance Describes how to optimize a database, and how to monitor performance. Lessons

• Optimizing 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:

• Describes how to tune the configuration of a database and collections for best performance.

• Describes 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:

• Describes 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 Analyzing Big Data with Cosmos DB This module describes how to use Azure Search and HDInsight with Cosmos DB to query and analyze big data. Lessons

• Integrating Cosmos DB with Azure search to optimize queries

• Analyzing data in a Cosmos DB database using Apache Spark

• Visualizing data in a Cosmos DB database

Lab: Querying and Analyzing Big Data with Cosmos DB

• Extending product search capabilities

• Performing end-of-month processing

• Visualizing sales data

• Exploring sales data

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

• Describes how to integrate Cosmos DB with Azure Search to perform efficient query processing over big data.

• Describes how to analyze big data held in Cosmos DB using Apache Spark.

• Describes how to visualize 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 analytics data

• Displaying rolling revenue for a given time period

After completing this module, students will be able to:

• Describes 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.