DP-200: Implementing an Azure Data Solution

Description

Duration: 5 days

During this three-day boot camp student will learn how to implement various data platform technologies to create solutions that are in line with business and technical requirements. Solutions included are on-premises, cloud, and hybrid data scenarios incorporating both relational and no-SQL Data.

Additional exploration will be done on How to implement data security with authentication, Authorization, Data policies and standards.

How to define and implement data solution monitoring for both the data storage and data processing activities.

It is recommended that students interested in this boot camp have previous knowledge, training, or experience with Azure Fundamentals.

This boot camp is intended for data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure.

 

Upon completion of this course, student will be able to:

  • Explain the evolving world of data
  • Survey the services in the Azure Data Platform
  • Identify the tasks that are performed by a data engineer
  • Describe the use cases for the cloud in a Case Study
  • Choose a data storage approach in Azure
  • Create an Azure Storage Account
  • Explain Azure Data Like Storage
  • Upload data into Azure Data Lake
  • Explain Azure Databricks
  • Describe the Team Data Science Process
  • Provision Azure Databricks and workspaces
  • Perform data preparation tasks
  • Create an Azure Cosmos DB database built to scale
  • Insert and query data in your Azure Cosmos DB database
  • Build a .NET Core app for Azure Cosmos DB in Visual Studio Code
  • Distribute your data globally with Azure Cosmos DB

 

Module 1: Azure for the Data Engineer

  • Explain the evolving world of data
  • Survey the services in the Azure Data Platform
  • Identify the tasks that are performed by a Data Engineer
  • Describe the use cases for the cloud in a Case Study

Labs Azure for the Data Engineer:

  • Azure for the Data Engineer
  • Identify the evolving world of data
  • Determine the Azure Data Platform Services
  • Identify the evolving world of data
  • Determine the Azure Data Platform Services
  • Identify tasks to be performed by a Data Engineer
  • Finalize the data engineering deliverables

 

Module 2: Working with Data Storage

Lessons

  • Choose a data storage approach in Azure
  • Create an Azure Storage Account
  • Explain Azure Data Lake storage
  • Upload data into Azure Data Lake

Lab: Working with Data storage

  • Choose a data storage approach in Azure
  • Create an Azure Storage Account
  • Explain Azure Data Lake Storage
  • Upload data into Azure Data Lake

 

Module 3: Enabling Team Based Data Science with Azure Databricks

Lessons

  • Explain Azure Databricks and Machine Learning Platforms
  • Describe the Team Data Science Process
  • Provision Azure Databricks and workspaces
  • Perform data preparation tasks

Lab: Enabling Team Based Data Science with Azure Databricks

  • Explain Azure Databricks and Machine Learning Platforms
  • Describe the Team Data Science Process
  • Provision Azure Databricks and Workspaces
  • Perform Data Preparation Tasks

 

Module 4: Building Globally Distributed databases with Cosmos DB

Lessons

  • Create an Azure Cosmos DB database built to scale
  • Insert and query data in your Azure Cosmos DB database
  • Provision a .NET Core app for Cosmos DB in Visual Studio
  • Distribute your data globally with Azure Cosmos DB

Lab: Building Globally Distributed Databases with Cosmos DB

  • Create an Azure Cosmos DB
  • Insert and Query data in Azure Cosmos DB
  • Build a .NET Core App for Azure Cosmos DB using VS Code
  • Distribute data globally with Azure Cosmos DB

 

Module 5: Working with Relational Data Stores in the Cloud

Lesson

  • SQL Database and SQL Data Warehouse
  • Provision and Azure SQL database to store data
  • Provision and load data into Azure SQL Data Warehouse

Lab: Working with relational Data Stores in the Cloud

  • Explain SQL Database and SQL Data Warehouse
  • Create and Azure SQL Database to store data
  • Provision and load data into Azure SQL Data Warehouse

 

Module 6: Performing Real-Time Analytics with Stream Analytics

Lessons

  • Explain data streams and event processing
  • Querying streaming data using Stream Analytics
  • How to process data with Azure Blob and Stream Analytics
  • How to process data with Event Hubs and Stream Analytics

Lab: Performing Real-/time Analytics with Stream Analytics

  • Explain data streams and event processing
  • Querying streaming data using Stream Analytics
  • Process data with Azure Blob and Stream Analytics
  • Process data with Event Hubs and Stream Analytics

 

Module 7: Orchestrating Data Movement with Azure Data Factory

Lessons

  • Explain how Azure Data Factory works
  • Create Linked Services and datasets
  • Create pipelines and activities
  • Azure Data Factory pipeline execution and triggers

Lab: Orchestrating Data Movement with Azure Data factory

  • Explain how Data Factory works
  • Create Linked services and Datasets
  • Create Pipelines and Activities
  • Azure Data Factory Pipeline Execution and Triggers

 

Module 8: Securing Azure Data Platforms

Lessons

  • Configuring Network Security
  • Configuring Authentication
  • Configuring Authorization
  • Auditing Security

Lab: Securing Azure Data Platforms

  • Configure network security
  • Configure Authentication
  • Control Network Access
  • Understand transport-level encryption with HTTPS
  • Understand Advanced Threat Detection

 

Module 9: Monitoring and Troubleshooting Data Storage and processing

  • Data Engineering troubleshooting approach
  • Azure Monitoring Capabilities
  • Troubleshoot common data issues
  • Troubleshoot common data processing issues

Lab: Monitoring and Troubleshooting Data Storage and Processing

  • Explain the Data Engineering troubleshooting approach
  • Explain the monitoring Capabilities that are available
  • Troubleshoot common data storage issues
  • Troubleshoot common data processing issues

 

 

Module 10: Integrating and Optimizing Data Platforms

  • Integrating data platforms
  • Optimizing data stores
  • Optimize streaming data
  • Manage disaster recovery

Labs: Integrating and Optimizing Data Platforms

  • Integrate Data Platforms
  • Optimize Data Stores
  • Optimize Streaming data stores
  • Mange Disaster Recovery