Implementing an Azure Data Solution

Learn To Use Azure To Meet Data Requirements

Learn how to use Azure for data solutions
Prepare for the Implementing an Azure Data Solution exam
Taught by Microsoft Certified Trainers
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.

Prerequisites

There are no prerequisites.

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.

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

About Milton Keynes

Milton Keynes

Milton Keynes also abbreviated as MK is a large town located in Buckinghamshire, England. It was designed as a new town on 23 January 1967 and also an administrative centre of Borough of Milton Keynes. It is located 45 miles that is 72 km away from north-west of London.

Various another town like Bletchley, Wolverton and Stony Stratford exist here along with other 15 villages and farmland. Milton Keynes took its name from existing “Village of Milton Keynes “that is few miles away from the planned centre.

History of Milton Keynes

Milton Keynes has a rich history with proof of human settlement that was found before starting the construction of this city in 1960’s. When UK government decided to establish Milton Keynes, most of the area was farmland, and undeveloped villages and the earlier history was incredibly rich. Until the 10^th century, there was no evidence of occupation in villages. During middle age, 18 villages were present that still form the heart of Milton Keynes districts. With the arrival of London and Birmingham Railway and Grand Junction canal in late 18^th and 19^th century, the area went through many changes and the new town of Wolverton, and New Bradwell emerged.

The greatest change in the history of Milton Keynes was when it was chosen to solve housing problems in London. Milton Keynes was planned as biggest towns and have an area of 89 square kilometres that became home to around 250,000 people. In the beginning, no building was allowed to be tall than the tallest tree, and later Milton Keynes Partnership changed it. Tallest building in Milton Keynes is 14 floors high. Its population will double by the year 2026.

Milton Keynes offers a broad range of opportunities to people to learn new things and get a better education. Bletchley Park code breakers brought innovation to the city in second world war. This team cracked secret codes of Germans. Milton Keynes is a destination that is always passionate about developing minds. It contains some of the best schools and colleges. Milton Keynes College offers a wide range of courses in different domains. It is one of the fastest growing college in the United Kingdom.

Open University offers contemporary learning where degree level education is provided to everyone. The headquarters of the university is located at Walton Hall in Milton Keynes. There is also University Centre Milton Keynes ( UCMK) which is a hub for higher education with new facilities and exciting courses in the middle of the city. This town also contains a solar-powered house that plays a significant role in the development of electric transport. Various courses, classes and opportunities are offered by Milton Keynes Theatre Creative Learning department to young people and adults to explore theatres including makeup, drama, acting and much more.

Sport

Milton Keynes has various professional teams in football, in ice hockey and in Formula one. It is also home to Xscape indoor ski slope, Formula Fast Indoor Karting Centre, Airkix Indoor Sky Diving facility and National Badminton Centre.

Economy

At Borough level, data of Milton Keynes economy, demography and politics is collected. Milton Keynes is one of the most successful economies in Southeast along with gross value added per capita index which was 47% higher than the national average. According to 2015 data, average wages place it in top five nationally.

Just 0.6% of businesses employ people more than 250 which include Open University, Volkswagen Group, Mercedes-Benz and Network Rail. Remaining enterprises around 81.5% employ near about 10 people. Milton Keynes professional, technical and scientific sector contributes large employment. Milton Keynes has a high number of business start-ups in England and start-up levels remained high even during the period of recession 2009/2010. Most of the population is younger. 22.6% of Borough population is under 16, 12.1% are aged 65+. According to 2011 census report, Milton Keynes Urban area comprises of 8.7% South Asian, 78.4% white, 3.5% Mixed Race, 7-5% Black, 1.2% Chinese, 6.7% other ethnic group and Asian.