Course DP-200T01-A: Implementing an Azure Data Solution

Microsoft

Course DP-200T01-A: Implementing an Azure Data Solution

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In this course, the students will implement various data platform technologies into solutions that are in-line with business and technical requirements, including on-premises, cloud, and hybrid data scenarios incorporating both relational and NoSQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.

The students will also explore how to implement data security, including authentication, authorization, data policies, and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing, and streaming data solutions.

Audience Profile

The primary audience for this course is Data Professionals, Data Architects, and Business Intelligence Professionals who want to learn about the data platform technologies that exist on Microsoft Azure.The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.

Prerequisites

Course outline

Module 1: Azure for the Data Engineer

Module Overview

This module explores how the world of data has evolved and how cloud data platform technologies are providing new opportunities for businesses to explore their data in different ways. The students will gain an overview of the various data platform technologies that are available and how a Data Engineer’s role and responsibilities has evolved to work in this new world to an organization’s benefit.

Lessons

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

Lab Sessions

Azure for the Data Engineer

Lab Lessons

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

After completing this module, students 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.

Module 2: Working with Data Storage

Module Overview

This module teaches the variety of ways to store data in Azure. The students will learn the basics of storage management in Azure, how to create a Storage Account, and how to choose the right model for the data want to be stored in the cloud. They will also understand how Data Lake storage can be created to support a wide variety of big data analytics solutions with minimal effort.

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 Sessions

Working with Data Storage

Lab Lessons

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

After completing this module, students will be able to:

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

Module Overview

This module introduces students to Azure Databricks and how a Data Engineer works with it to enable an organization to perform Team Data Science projects. They will learn the fundamentals of Azure Databricks and Apache Spark notebooks; how to provision the service and workspaces; and how to perform data preparation task that can contribute to the data science project.

Lessons

Explain Azure Databricks
Work with Azure Databricks
Read data with Azure Databricks
Perform transformations with Azure Databricks

Lab Sessions

Enabling Team Based Data Science with Azure Databricks

Lab Lessons

Explain Azure Databricks
Work with Azure Databricks
Read data with Azure Databricks
Perform transformations with Azure Databricks

After completing this module, students will be able to:

Explain Azure Databricks.
Work with Azure Databricks.
Read data with Azure Databricks.
Perform transformations with Azure Databricks.

Module 4: Building Globally Distributed Databases with Cosmos DB

Module Overview

In this module, students will learn how to work with NoSQL data using Azure Cosmos DB. They will learn how to provision the service, how they can load and interrogate data in the service using Visual Studio Code extensions, and the Azure Cosmos DB .NET Core SDK. They will also learn how to configure the availability options so that users are able to access the data from anywhere in the world.

Lessons

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 Cosmos DB in Visual Studio Code
Distribute data globally with Azure Cosmos DB

Lab Sessions

Building Globally Distributed Databases with Cosmos DB

Lab Lessons

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

After completing this module, students will be able to:

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 data globally with Azure Cosmos DB.

Module 5: Working with Relational Data Stores in the Cloud

Module Overview

In this module, students will explore the Azure relational data platform options, including SQL Database and SQL Data Warehouse. The students will be able explain why they would choose one service over another, and how to provision, connect, and manage each of the services.

Lessons

Use Azure SQL Database
Describe Azure SQL Data Warehouse
Creating and Querying an Azure SQL Data Warehouse
Use PolyBase to Load Data into Azure SQL Data Warehouse

Lab Sessions

Working with Relational Data Stores in the Cloud

Lab Lessons

Use Azure SQL Database
Describe Azure SQL Data Warehouse
Creating and Querying an Azure SQL Data Warehouse
Use PolyBase to Load Data into Azure SQL Data Warehouse

After completing this module, students will be able to:

Use Azure SQL Database.
Describe Azure Data Warehouse.
Create and Query an Azure SQL Data Warehouse.
Use PolyBase to Load Data into Azure SQL Data Warehouse.

Module 6: Performing Real-Time Analytics with Stream Analytics

Module Overview

In this module, students will learn the concepts of event processing and streaming data and how this applies to Events Hubs and Azure Stream Analytics. The students will then set up a stream analytics job to stream data and learn how to query the incoming data to perform analysis of the data. Finally, they will learn how to manage and monitor running jobs.

Lessons

Explain data streams and event processing
Data Ingestion with Event Hubs
Processing Data with Stream Analytics Jobs

Lab Sessions

Performing Real-Time Analytics with Stream Analytics

Lab Lessons

Explain data streams and event processing
Data Ingestion with Event Hubs
Processing Data with Stream Analytics Jobs

After completing this module, students will be able to:

Be able to explain data streams and event processing.
Understand Data Ingestion with Event Hubs.
Understand Processing Data with Stream Analytics Jobs.

Module 7: Orchestrating Data Movement with Azure Data Factory

Module Overview

In this module, students will learn how Azure Data Factory can be used to orchestrate the data movement and transformation from a wide range of data platform technologies. They will be able to explain the capabilities of the technology and be able to set up an end to end data pipeline that ingests and transforms data.

Lessons

Explain how Azure Data Factory works
Azure Data Factory Components
Azure Data Factory and Databricks

Lab Sessions

Orchestrating Data Movement with Azure Data Factory

Lab Lessons

Explain how Data Factory Works
Azure Data Factory Components
Azure Data Factory and Databricks

After completing this module, students will be able to:

Understand Azure Data Factory and Databricks.
Understand Azure Data Factory Components.
Be able to explain how Azure Data Factory works.

Module 8: Securing Azure Data Platforms

Module Overview

In this module, students will learn how Azure provides a multi-layered security model to protect data. The students will explore how security can range from setting up secure networks and access keys, to defining permission, to monitoring across a range of data stores.

Lessons

An introduction to security
Key security components
Securing Storage Accounts and Data Lake Storage
Securing Data Stores
Securing Streaming Data

Lab Sessions

Securing Azure Data Platforms

Lab Lessons

An introduction to security
Key security components
Securing Storage Accounts and Data Lake Storage
Securing Data Stores
Securing Streaming Data

After completing this module, students will be able to:

Have an introduction to security.
Understand key security components.
Understand securing Storage Accounts and Data Lake Storage.
Understand securing Data Stores.
Understand securing Streaming Data.

Module 9: Monitoring and Troubleshooting Data Storage and Processing

Module Overview

In this module, the students will get an overview of the range of monitoring capabilities that are available to provide operational support should there be issue with a data platform architecture. They will explore the common data storage and data processing issues. Finally, disaster recovery options are revealed to ensure business continuity.

Lessons

Explain the monitoring capabilities that are available
Troubleshoot common data storage issues
Troubleshoot common data processing issues
Manage disaster recovery

Lab Sessions

Monitoring and Troubleshooting Data Storage and Processing

Lab Lessons

Explain the monitoring capabilities that are available
Troubleshoot common data storage issues
Troubleshoot common data processing issues
Manage disaster recovery

After completing this module, students will be able to:

Explain the monitoring capabilities that are available.
Troubleshoot common data storage issues.
Troubleshoot common data processing issues.
Manage disaster recovery.

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