This event has been UPDATED since it was first published. View the UPDATED & Detailed Designing Azure Data Solution(DP-201)Training Certification course for beginners Information here.

• All Published Ticket Prices are in US Dollars
• The course will be taught in English language

Wknds Designing Azure Data Solution(DP-201) Training Certification Course is Instructor-led and guided and is being delivered November 28, 2020 - December 20, 2020 US Pacific Time for 16 hours over 4 weekends, 8 sessions, 2 sessions per week, 2 hours per session.

• During this course, 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, NoSQL, 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.

Wknds Designing Azure Data Solution(DP-201) Training Certification Course Schedule

• November 28, 2020 - December 20, 2020 US Pacific time
• 4 Weekends | 2 Hours on Saturdays, 2 Hours on Sundays every week US Pacific time
• 7:30 AM - 9:30 AM US Pacific time each of those days
• Please click here to add your city name and check your local date and time for the first session to be held on November 28, 2020 at 7.30 AM US Pacific Time

Features and Benefits

• 4 Weekends, 8 sessions, 16 hours of total Instructor-led and guided training
• Training material, instructor handouts and access to useful resources on the cloud provided
• Practical Hands-on Lab exercises provided
• Real-life Scenarios

Course Objectives

During this course you will learn:

• Data Platform Architecture Considerations
• Azure Batch Processing Reference Architectures
• Azure Real-Time Reference Architectures
• Data Platform Security Design Considerations
• Designing for Resiliency and Scale
• Design for Efficiency and Operations

Who can take this course

The primary 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

Prerequisites

Before attending this course, students must have:

• Must have the complete Azure Fundamentals knowledge
• Azure Data Engineer knowledge

If you do not meet the prerequisites, please let us know, we can enroll you in another class where you can learn the prerequisites in parallel even as you take this course. There will be an extra cost associated.

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

After completing this module, students will be able to:

• Design with Security in mind
• Consider performance and scalability
• Design for availability and recoverability
• Design for efficiency and operations

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

After completing this module, students will be able to:

• Core Principles of Creating Architectures
• 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

Case study

Module 3: Azure Real-Time Reference Architectures

• In this module, students 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
• 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, students will learn how to incorporate security into an architecture design and learn the key decision points in Azure provides to help create a secure environment through all the layers of your architecture.

Lessons:

• Defense in Depth Security Approach
• Identity Management
• Infrastructure Protection
• Encryption Usage
• Network Level Protection
• Application Security

After completing this module, students will be able to:

• Defense in Depth Security Approach
• Identity Management
• Infrastructure Protection
• Encryption Usage
• Network Level Protection
• Application Security

Module 5: Designing for Resiliency and Scale

• In this module, students 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:

• Adjust Workload Capacity by Scaling
• Optimize Network Performance
• Design for Optimized Storage and Database Performance
• Identifying Performance Bottlenecks
• 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
• Identifying Performance Bottlenecks
• 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

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