In this course, 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 No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.

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.

Course are classified: Microsoft Certified Azure Fundamentals and Implementing an Azure Data Solution

Upcoming Dates	Class Times	Class Format	Price
M,T, F February 1st – 28 2023 November 20th 2023	12:00 pm – 1:30 pm	Instructor-Led Virtual Live Class	$2,400

Purpose Of the Course

The course will develop highly skilled Microsoft Azure data engineers, sales of cloud solutions and Data Engineer to fill the skill-gap in the job market

 

Entrance requirement Description

Acceptance into The Bright Technology Training is competitive and all students seeking admission must meet all applicable requirements. In order to be considered for admission, all applicants must:

1. Complete and submit an admissions application along with the required non-refundable $25 fee;
2. Provide proof of U.S. citizenship or Permanent Residence status.
3. Provide proof of a U. S. high school diploma, GED, or the recognized equivalent
4. Interview with the admissions officer,
5. Possess basic keyboard skills (A minimum of 35 WPM is required),
6. Provide proof of College Degree in any disciplines for students seeking admission into Data Analytic Program
7. Provide proof of at least one year of professional work experience in an office environment.
8. Pass the Bright Technology Training computer-based Computer Literacy Test (CLT); and,
9. Complete and sign an Enrollment Agreement.

 

 

Course Outline

Microsoft Certified Azure Fundamentals — 16 Hour

Understand cloud concepts

Describe the benefits and considerations of using cloud services

• understand terms such as high availability, scalability, elasticity, agility, fault tolerance, and disaster recovery
• understand the principles of economies of scale
• understand the differences between Capital Expenditure (CapEx) and Operational

Expenditure (OpEx)

• understand the consumption-based model

Describe the differences between Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS)

• describe Infrastructure-as-a-Service (IaaS)
• describe Platform-as-a-Service (PaaS)
• describe Software-as-a-Service (SaaS)
• compare and contrast the three different service types

 

Describe the differences between public, private and hybrid cloud models

• describe public cloud
• describe private cloud
• describe hybrid cloud
• compare and contrast the three different cloud models

Understand core Azure services

Understand the core Azure architectural components

• describe Regions
• describe Availability Zones
• describe Resource Groups
• describe Azure Resource Manager
• describe the benefits and usage of core Azure architectural components

Describe some of the core products available in Azure

• describe products available for Compute such as Virtual Machines, Virtual Machine Scale
• Sets, App Service Functions, Azure Container Instances (ACI) and Azure Kubernetes

Service (AKS)

• describe products available for Networking such as Virtual Network, Load Balancer, VPN Gateway, Application Gateway and Content Delivery Network
• describe products available for Storage such as Blob Storage, Disk Storage, File Storage,

and Archive Storage

• describe products available for Databases such as Cosmos DB, Azure SQL Database,

Azure Database for MySQL, Azure Database for PostgreSQL, Azure Database Migration service

• describe the Azure Marketplace and its usage scenarios

Describe some of the solutions available on Azure

• describe Internet of Things (IoT) and products that are available for IoT on Azure such as IoT Hub and IoT Central
• describe Big Data and Analytics and products that are available for Big Data and

Analytics such as SQL Data Warehouse, HDInsight, and Azure Databricks

• describe Artificial Intelligence (AI) and products that are available for AI such as Azure

Machine Learning Service and Studio

• describe Serverless computing and Azure products that are available for serverless computing such as Azure Functions, Logic Apps, and Event Grid
• describe DevOps solutions available on Azure such as Azure DevOps and Azure DevTest Labs
• describe the benefits and outcomes of using Azure solutions

 

Understand Azure management tools

• understand Azure tools such as Azure Portal, Azure PowerShell, Azure CLI and Cloud Shell
• understand Azure Advisor

Understand security, privacy, compliance, and trust

Understand securing network connectivity in Azure

• describe Network Security Groups (NSG)
• describe Application Security Groups (ASG)
• describe User Defined Rules (UDR)
• describe Azure Firewall
• describe Azure DDoS Protection
• choose an appropriate Azure security solution

Describe core Azure Identity services

• understand the difference between authentication and authorization
• describe Azure Active Directory
• describe Azure Multi-Factor Authentication

Describe security tools and features of Azure

• describe Azure Security Center
• understand Azure Security Center usage scenarios
• describe Key Vault
• describe Azure Information Protection (AIP)
• describe Azure Advanced Threat Protection (ATP)

Describe Azure governance methodologies

• describe policies and initiatives with Azure Policy
• describe Role-Based Access Control (RBAC)
• describe Locks
• describe Azure Advisor security assistance
• describe Azure Blueprints

Understand monitoring and reporting options in Azure

• describe Azure Monitor
• describe Azure Service Health
• understand the use cases and benefits of Azure Monitor and Azure Service Health

Understand privacy, compliance and data protection standards in Azure

• understand industry compliance terms such as GDPR, ISO and NIST
• understand the Microsoft Privacy Statement
• describe the Trust center
• describe the Service Trust Portal
• describe Compliance Manager
• determine if Azure is compliant for a business need

Understand Azure pricing and support

Understand Azure subscriptions

• describe an Azure subscription
• understand the uses and options with Azure subscriptions such access control and offer types
• understand subscription management using Management groups

Understand planning and management of costs

• understand options for purchasing Azure products and services
• understand options around Azure Free account
• understand the factors affecting costs such as resource types, services, locations, ingress and egress traffic understand Zones for billing purposes
• understand the Pricing calculator
• understand the Total Cost of Ownership (TCO) calculator
• understand best practices for minimizing Azure costs such as performing cost analysis, creating spending limits and quotas, using tags to identify cost owners, using Azure reservations and using Azure Advisor recommendations
• describe Azure Cost Management

Understand the support options available with Azure

• understand support plans that are available such as Dev, Standard, Professional Direct and Premier
• understand how to open a support ticket
• understand available support channels outside of support plan channels
• describe the Knowledge Center

Describe Azure Service Level Agreements (SLAs)

• describe a Service Level Agreement (SLA)
• understand Composite SLAs
• understand how to determine an appropriate SLA for an application

Understand service lifecycle in Azure

• understand public and private preview features
• understand the term General Availability (GA)
• understand how to monitor feature updates and product changes

 

 

Implementing an Azure Data Solution-    24 hours

Course outline

Module 1: Azure for the Data Engineer

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 : 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

Module 2: Working with Data Storage

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 : 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

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 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

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

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 : 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

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

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 : 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
• 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

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 : 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
• Understand Data Ingestion with Event Hubs
• Understand 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

After completing this module, students will:

• 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

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 : 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:

• 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

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 : 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