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DP-201: Designing an Azure Data Solution Course Outline

 (2 days)

This course has an expected release date of May 02, 2019

Overview
In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data.

The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions.

Prerequisites
In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:

Azure fundamentals

DP-200: Implementing an Azure Data Solution

Audience profile
The 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.

Special Note to New Hampshire Residents
This course has not yet been approved by the State's Department of Education. Please contact us to get an update as to when the class should be available in New Hampshire

At course completion
Describe the core principles for creating architectures
Design with Security in mind
Consider performance and scalability
Design for availability and recoverability
Design for efficiency and operations
Understand the course Case Study
Describe Lambda architectures from a Batch Mode Perspective
Design an Enterprise BI solution in Azure
Automate enterprise BI solutions in Azure
Architect an Enterprise-grade conversational bot in Azure
Lambda architectures for a Real-Time Mode Perspective
Architect a stream processing pipeline with Azure Stream Analytics
Design a stream processing pipeline with Azure Databricks
Create an Azure IoT reference architecture
Defense in Depth Security Approach
Network Level Protection
Identity Protection
Encryption Usage
Advanced Threat Protection
Adjust Workload Capacity by Scaling
Optimize Network Performance
Design for Optimized Storage and Database Performance
Design a Highly Available Solution
Incorporate Disaster Recovery into Architectures
Design Backup and Restore strategies
Maximize the Efficiency of your Cloud Environment
Use Monitoring and Analytics to Gain Operational Insights
Use Automation to Reduce Effort and Error

Course Outline

Module 1: Data Platform Architecture Considerations
In this module, the students will learn how to design and build secure, scalable and performant solutions in Azure by examining the core principles found in every good architecture. They will learn how using key principles throughout your architecture regardless of technology choice, can help you design, build, and continuously improve your architecture for an organizations benefit.

Lessons
Core Principles of Creating Architectures
Design with Security in Mind
Performance and Scalability
Design for availability and recoverability
Design for efficiency and operations
Case Study
Lab : Case Study
Core principles for creating architectures
Design with security in mind
Consider performance and scalability
Design for availability and recoverability
Design for efficiency and operations

After completing this module, students will be able to:
Describe the core principles for creating architectures
Design with Security in mind
Consider performance and scalability
Design for availability and recoverability
Design for efficiency and operations
Understand the course Case Study

Module 2: Azure Batch Processing Reference Architectures
In this module, the student will learn the reference design and architecture patterns for dealing with the batch processing of data. The student will be exposed to dealing with the movement of data from on-premises systems into a cloud data warehouse and how it can be automated. The student will also be exposed to an AI architecture and how the data platform can integrate with an AI solution.

Lessons
Lambda architectures from a Batch Mode Perspective
Design an Enterprise BI solution in Azure
Automate enterprise BI solutions in Azure
Architect an Enterprise-grade Conversational Bot in Azure
Lab : Architect an Enterprise-grade Conversational Bot in Azure
Lambda architectures from a Batch Mode Perspective
Designing an Enterprise BI solution in Azure
Automate an Enterprise BI solution in Azure
Automate an Enterprise BI solution in Azure

After completing this module, students will be able to:
Describe Lambda architectures from a Batch Mode Perspective
Design an Enterprise BI solution in Azure
Automate enterprise BI solutions in Azure
Architect an Enterprise-grade conversational bot in Azure

Module 3: Azure Real-Time Reference Architectures
In this module, the student will learn the reference design and architecture patterns for dealing with streaming data. They will learn how streaming data can be ingested by Event Hubs and Stream Analytics to deliver real-time analysis of data. They will also explore a data science architecture the streams data into Azure Databricks to perform trend analysis. They will finally learn how an Internet of Things (IoT) architecture will require data platform technologies to store data.

Lessons
Lambda architectures for a Real-Time Perspective
Lambda architectures for a Real-Time Perspective
Design a stream processing pipeline with Azure Databricks
Create an Azure IoT reference architecture
Lab : Azure Real-Time Reference Architectures
Describe Lambda architectures for a Real-Time Mode Perspective
Architect a stream processing pipeline with Azure Stream Analytics
Design a stream processing pipeline with Azure Databricks
Create an Azure IoT reference architecture

After completing this module, students will be able to:
Lambda architectures for a Real-Time Mode Perspective
Architect a stream processing pipeline with Azure Stream Analytics
Design a stream processing pipeline with Azure Databricks
Create an Azure IoT reference architecture

Module 4: Data Platform Security Design Considerations
In this module, the student will learn how to incorporate security into your architecture design and discover the tools that Azure provides to help you create a secure environment through all the layers of your architecture.

Lessons
Defense in Depth Security Approach
Network Level Protection
Identity Protection
Encryption Usage
Advanced Threat Protection
Lab : Data Platform Security Design Considerations
Defense in Depth Security Approach
Network Level Protection
Identity Protection
Encryption Usage
Advanced Threat Protection

After completing this module, students will be able to:
Defense in Depth Security Approach
Network Level Protection
Identity Protection
Encryption Usage
Advanced Threat Protection

Module 5: Designing for Resiliency and Scale
In this module, student will learn scaling services to handle load. They will learn how identifying network bottlenecks and optimizing your storage performance are important to ensure your users have the best experience. They will also learn how to handle infrastructure and service failure, recover from the loss of data, and recover from a disaster by designing availability and recoverability into your architecture.

Lessons
Design Backup and Restore strategies
Optimize Network Performance
Design for Optimized Storage and Database Performance
Design for Optimized Storage and Database Performance
Incorporate Disaster Recovery into Architectures
Design Backup and Restore strategies
Lab : Designing for Resiliency and Scale
Adjust Workload Capacity by Scaling
Optimize Network Performance
Design for Optimized Storage and Database Performance
Design a Highly Available Solution
Incorporate Disaster Recovery into Architectures
Design Backup and Restore strategies

After completing this module, students will be able to:
Adjust Workload Capacity by Scaling
Optimize Network Performance
Design for Optimized Storage and Database Performance
Design a Highly Available Solution
Incorporate Disaster Recovery into Architectures
Design Backup and Restore strategies

Module 6: Design for Efficiency and Operations
In this module, students will learn how to design an Azure architecture that is operationally-efficient and minimizes costs by reducing spend, they will understand how to design architectures that eliminates waste and gives them full visibility into what is being utilized in your organizations Azure environment.

Lessons
Maximizing the Efficiency of your Cloud Environment
Use Monitoring and Analytics to Gain Operational Insights
Use Automation to Reduce Effort and Error
Lab : Design for Efficiency and Operations
Maximize the Efficiency of your Cloud Environment
Use Monitoring and Analytics to Gain Operational Insights
Use Automation to Reduce Effort and Error

After completing this module, students will be able to:
Maximize the Efficiency of your Cloud Environment
Use Monitoring and Analytics to Gain Operational Insights
Use Automation to Reduce Effort and Error

View outline in Word

ADP201

Attend hands-on, instructor-led DP-201: Designing an Azure Data Solution training classes at ONLC's more than 300 locations. Not near one of our locations? Attend these same live classes from your home/office PC via our Remote Classroom Instruction (RCI) technology.

For additional training options, check out our list of Azure Courses and select the one that's right for you.

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Fee:  $1195

Savings options:

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