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

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: Azure for the Data Engineer

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

This module teaches the variety of ways to store data in Azure. The Student 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 you want to store 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.

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 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

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 learn how to perform data preparation task that can contribute to the data science project.

Explain Azure Databricks

Work with Azure Databricks

Read data with Azure Databricks

Perform transformations with Azure Databricks

Lab: Enabling Team Based Data Science with Azure Databricks

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

In this module, students will learn how to work with NoSQL data using Azure Cosmos DB. They will learn how to provision the service, and 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.

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 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

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

Distribute your data globally with Azure Cosmos DB

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

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: Working with Relational Data Stores in the Cloud

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

Creating and Querying an Azure SQL Data Warehouse

Using PolyBase to Load Data into Azure SQL Data Warehouse

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, you will learn how to manage and monitor running jobs.

Explain data streams and event processing

Data Ingestion with Event Hubs

Processing Data with Stream Analytics Jobs

Lab: Performing Real-Time Analytics with Stream Analytics

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:

Explain data streams and event processing

Data Ingestion with Event Hubs

Processing Data with Stream Analytics Jobs

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.

Explain how Azure Data Factory works

Azure Data Factory Components

Azure Data Factory and Databricks

Lab: Orchestrating Data Movement with Azure Data Factory

Explain how Data Factory Works

Azure Data Factory Components

Azure Data Factory and Databricks

After completing this module, students will be able to:

Azure Data Factory and Databricks

Azure Data Factory Components

Explain how Azure Data Factory works

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

An introduction to security

Key security components

Securing Storage Accounts and Data Lake Storage

Securing Data Stores

Securing Streaming Data

Lab: Securing Azure Data Platforms

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:

An introduction to security

Key security components

Securing Storage Accounts and Data Lake Storage

Securing Data Stores

Securing Streaming Data

In this module, the student 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.

Explain the monitoring capabilities that are available

Troubleshoot common data storage issues

Troubleshoot common data processing issues

Manage disaster recovery

Lab: Monitoring and Troubleshooting Data Storage and Processing

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