20777: Implementing Microsoft Azure Cosmos DB Solutions Training

20777: Implementing Microsoft Azure Cosmos DB Solutions Training is developed to make familiarize with the Azure Cosmos DB, building and implementing SQL API database apps. This technical course teaches individuals to apply server-side operations, monitor, and optimize performance. It elaborates on designing and applying a graph database, and it also contains assessing big data, querying, and applying stream processes with Cosmos DB. Our Enterprise training program allows a team up-gradation with a skill set that leads to the firm's overall development. By the end of the course, trainees will learn to demonstrate the overall structure and purpose of Azure Cosmos DB. It helps them create user-defined functions, triggers, and stored procedures. This training program is best for database architects and developers who plan to apply big data solutions on Azure using Cosmos DB.

This training is designed based on the objectives of the course variant 20777A

• Learning about the architecture and purpose of Azure Cosmos DB.
• Monitoring performance and tuning a database.
• Designing collections and documents to meet business requirements and learning how to create applications that utilize these documents using SQL API.
• Creating triggers, stored procedures, and user-defined functions.
• Using Power BI, Azure Databricks, HDInsight, and Azure Search with Cosmos DB to analyze and query big data.
• Learning how to stream data using Cosmos DB as both a sink and source.
• Describing how to use Cosmos DB to create efficient Graph database models.

This training is designed for database professionals, including database architects and developers, information workers, and IT professionals who want to learn how to use Cosmos DB to implement big data solutions on Azure.

• 1. Introduction to Azure Cosmos DB

Describe the purpose and architecture of 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 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.
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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.
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.
3. Implementing Server Side Operations
Describe how to create user-defined functions, stored procedures, and triggers.
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.
4. Optimizing and monitoring performance
Describe how to optimize a database, and how to monitor performance.
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:
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.
5. Designing and Implementing a Graph Database
This module describes how to create efficient graph database models using Cosmos DB.
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.
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.
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:
Describe how to integrate Cosmos DB with Azure Search to perform efficient query processing over big data.
Describe how to analyze big data held in Cosmos DB using Apache Spark.
Describe how to visualize data in Cosmos DB using Jupyter notebooks, Power BI, and Azure Databricks.
7. Implementing Stream Processing with Cosmos DB
This module describes how to use Cosmos DB as a source and sink for streaming data.
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.