A Quick Glance

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    Learn how to use Azure for data solutions

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    Prepare for the Implementing an Azure Data Solution exam

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    Taught by Microsoft Certified Trainers

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    Includes official Microsoft material

Who should take this course

Data professionals, data architects, and business intelligence experts who want to learn more about Microsoft Azure's data platform technologies and Develop applications that deliver content from Microsoft Azure's data platform technologies.

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Prerequisites

There are no prerequisites.

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  Course Overview

In this course, delegates will learn how to implement various data platform technologies in solutions that meet business and technical needs, including on-premise, cloud, and hybrid data scenarios, which include both relational and no-SQL data. Delegates will also learn how to process data using a range of technologies and languages ​​for both streaming and batch data.

This course explores how to implement data security, including authentication, authorisation, data policies and standards,  and implement data solution monitoring for both data storage and data processing. Eventually, they will manage and troubleshoot Azure data solutions, including optimising and restoring large volumes of data, batch processing, and streaming data solutions.

This role-based course can be used to prepare for certification as a Microsoft Azure Data Engineer.

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  Course Content

Module 1: Azure for the Data Engineer

This module explores how the world of data has evolved and how cloud datAudiencea 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

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: 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

Module 2: Working with Data Storage

 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.

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 a Storage Account
  • Explain Data Lake Storage
  • Upload data into Data Lake Store

 

Module 3: Enabling Team Based Data Science with Azure Databricks

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.

Lessons

  • 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

 

Module 4: Building Globally Distributed Databases with Cosmos DB

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.

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 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

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.

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: 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

 

Module 6: Performing Real-Time Analytics with Stream Analytics

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.

Lessons

  • 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

 

Module 7: Orchestrating Data Movement with Azure Data Factory

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: Orchestrating Data Movement with Azure Data Factory

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

 

Module 8: Securing Azure Data Platforms

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.

Lessons

  • 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

 

Module 9: Monitoring and Troubleshooting Data Storage and Processing

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.

Lessons

  • 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
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About Carlisle

Carlisle, a city in Cumbria, is also the managerial centre of the City of Carlisle region in North West England. It is the main settlement in the county of Cumbria and helps as the managerial centre for both Carlisle City Council and Cumbria County Council. At the time of the 2001 survey, the population of Carlisle was 71,773. In 2011, the city's population had increased to 75,306, with 107,524 in the wider city.

The early history of Carlisle is noticeable as a Roman payment, recognised to serve the forts on Hadrian's Wall. In the Middle Ages, because of its nearness to the Realm of Scotland, Carlisle industrialised meaningfully. The armed stranglehold, Carlisle Castle, was built in 1092 by William Rufus, and once added as a custodial for Mary, Queen of Scots. The castle now relatives the Duke of Lancaster's Regiment and the Border Regiment Museum. In the 12th century, Henry I allowed the building of a priory in Carlisle. The town produced the rank of a city when its diocese was formed in 1133, and the cloister industrialised Carlisle Cathedral.

Governance:

Carlisle has detained city status since the Middle Ages. Also, it kept its status as an area constituency or governmental borough for centuries, at one time returning two MPs. In 1835 it became a municipal borough and was later upgraded to a  borough status in 1914. The city's boundaries have changed several times since 1835 the final time in 1974. 

The municipal area surrounded many parts of parishes which were combined into a single civil parish of Carlisle in 1904. The currently present urban area is considered as an unparished area. Carlisle had in 2002 made an unsuccessful attempt to grow to a Lord Mayoralty. An iconic building that stands tallest in Carlisle may be demolished, and the area nearby to it rehabilitated.

Climate:

Carlisle practices an oceanic climate. In January 2005 Carlisle was hit by strong wind storms and torrential rains. On Saturday 8 January 2005 all roads into Carlisle were shut owed to severe flooding, the worst since 1822, which produced three deaths. Less severe but still significant flooding occurred in 2009, but due to Storm Desmond. Carlisle experienced even worse flooding than 2005 between Friday 4 and Sunday 6 December 2015. During this time, nearly 36 hours of nonstop precipitation broke flood defences. This left several areas submerged including Bitts Park, Hardwicke Circus and Warwick Road. This left the famous Sands Centre, stranded from the rest of the city. As several other areas of Cumbria were also severely pretentious, all trains to Scotland were postponed forever. The trains on the West Coast Principal went no further than Preston. Prime Minister David Cameron stayed the city on 7 December 2015 to measure the damage.

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