Designing an Azure Data Science Solution on Azure DP-201

Advanced 609(5 Ratings)
English
What will you learn?
  • Understand the core principles of creating architectures
  • Describe Lambda architectures for a Real-Time Mode Perspective
  • Design for Optimized Storage and Database Performance
  • Incorporate Disaster Recovery into Architectures
  • Architect a stream processing pipeline with Azure Stream Analytics
  • Architect an Enterprise-grade conversational bot in Azure

Live training
Prerequisites
  • This course is for Data Professionals, Data Architects, and Business Intelligence Professionals
  • Should have completed DP-200: Implementing an Azure Data Solution
Description

In this 2 Days training which is Designing an Azure Data Science Solution on Azure DP-201. You will learn to design Azure data storage solutions; design data processing solutions; and design for data security and compliance.

Module 1: Data Platform Architecture Considerations

This course will start how to design and build secure, scalable, and performant solutions in Azure by examining the core principles found in every good architecture. Students will learn how to use key principles throughout architecture, regardless of technology choice, can help you design, build, and continuously improve the architecture for an organization's benefit.

Lab : Case Study

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

Now you can

  • Consider performance and scalability
  • Design for availability and recoverability
  • Design for efficiency and operations

Module 2: Azure Batch Processing Reference Architectures

In this module of Azure Batch Processing Reference Architectures it deals with batch processing of data. Learn how to Design an Enterprise BI solution in Azure, Automate enterprise BI solutions in Azure. Lastly, Architect an Enterprise-grade Conversational Bot in Azure.

Lab : Architect an Enterprise-grade Conversational Bot in Azure

  • Designing an Enterprise BI solution in Azure
  • Automate an Enterprise BI solution in Azure
  • Automate an Enterprise BI solution in Azure

Now you can

  • Describe Lambda architectures from a Batch Mode Perspective
  • Design an Enterprise BI solution in Azure
  • Automate enterprise BI solutions in Azure

Module 3: Azure Real-Time Reference Architectures

This module contains about the reference design and architecture patterns for dealing with streaming data. Also learn how to Architect a stream processing pipeline with Azure Stream Analytics. Learn hnow to design a stream processing pipeline with Azure Databricks. Finally, create an Azure IoT reference architecture.

Lab : Azure Real-Time Reference Architectures

  • Architect a stream processing pipeline with Azure Stream             Analytics
  • Design a stream processing pipeline with Azure Databricks
  • Create an Azure IoT reference architecture

Now you can

  • Describe Lambda architectures for a Real-Time Mode Perspective
  • Architect a stream processing pipeline with Azure Stream Analytics

Module 4: Data Platform Security Design Considerations

In this module, the students will learn about the defense in Depth Security Approach, Identity Management, Infrastructure Protection, Encryption Usage, Network Level Protection and, Application Security.

Lab : Data Platform Security Design Considerations

  • Defense in Depth Security Approach
  • Identity Protection

Now you can

  • Defense in Depth Security Approach
  • Identity Management
  • Infrastructure Protection

Module 5: Designing for Resiliency and Scale

In this module we will teach scaling services to handle load. They will learn how identifying network bottlenecks and optimizing storage performance are important to ensure 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 the architecture.

Lab : Designing for Resiliency and Scale

  • Adjust Workload Capacity by Scaling
  • Design for Optimized Storage and Database Performance
  • Design a Highly Available Solution
  • Incorporate Disaster Recovery into Architectures

Now you can

  • Design for Optimized Storage and Database Performance
  • Identify Performance Bottlenecks
  • Design a Highly Available Solution

Module 6: Design for Efficiency and Operations

This module will conclude with Maximizing the Efficiency of your Cloud Environment. Learn how to use monitoring and Analytics to Gain Operational Insights and 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

Now you can

  • Maximize the Efficiency of your Cloud Environment
  • Use Monitoring and Analytics to Gain Operational Insights
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  • Certificate of Completion
  • Flexible Schedule
  • 100% online courses