Designing an Azure Data Solution (DP-201)

Become The First Generation Leader of The Designing an Azure Data Solution (DP-201) Technologies Revolution.

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Online-Live

Format

2 Months

Recommended 5-6 Hrs/Week

Aug 21, 2020

Start Date

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Syllabus

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 architecture, regardless of technology choice, can help you design, build, and continuously improve the architecture for an organization's 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
  • 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:
  • Design with security in mind
  • Consider performance and scalability
  • Design for availability and recoverability
  • Design for efficiency and operations
Azure Batch Processing Reference Architectures

In this module, students 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 students 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
  • 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:
  • Understand the 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
Azure Real-Time Reference Architectures

In this module, the 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 that 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
  • Describe 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
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
After completing this module, students will be able to:
  • 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
Data Platform Security Design Considerations

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

Lessons
  • Defense in Depth Security Approach
  • Identity Management
  • Infrastructure Protection
  • Encryption Usage
  • Network Level Protection
  • Application Security
Lab : Data Platform Security Design Considerations
  • Defense in Depth Security Approach
  • Identity Protection
After completing this module, students will understand the following:
  • Defense in Depth Security Approach
  • Identity Management
  • Infrastructure Protection
  • Encryption Usage
  • Network Level Protection
  • Application Security
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 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.

Lessons
  • Adjust Workload Capacity by Scaling
  • Optimize Network Performance
  • Design for Optimized Storage and Database Performance
  • Identify Performance Bottlenecks
  • Design a Highly Available Solution
  • Incorporate Disaster Recovery into Architectures
  • Design Backup and Restore strategies
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
After completing this module, students will be able to:
  • Adjust Workload Capacity by Scaling
  • Optimize Network Performance
  • Design for Optimized Storage and Database Performance
  • Identify Performance Bottlenecks
  • Design a Highly Available Solution
  • Incorporate Disaster Recovery into Architectures
  • Design Backup and Restore strategies
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 and they will understand how to design architectures that eliminate waste and gives them full visibility into what is being utilized in the organization's 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

Certification

Executive Program in Designing an Azure Data Solution (DP-201) Certified by Microsoft.

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Students Placed in Top MNC's

Platforms Covered

Solidity

VM

A virtual machine is a computer file, typically called an image, which behaves like an actual computer. In other words, creating a computer within a computer. It runs in a window, much like any other programme, giving the end user the same experience on a virtual machine as they would have on the host operating system itself.

databricks

Azure Databricks

Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services platform. For a big data pipeline, the data (raw or structured) is ingested into Azure through Azure Data Factory in batches, or streamed near real-time using Kafka, Event Hub, or IoT Hub.

Solidity

Azure Storage

Azure Storage is a Microsoft-managed cloud storage service, that provides highly available, durable, scalable and redundant storage, at a fraction of the cost, if you were to manage it manually.

Solidity

Azure Virtual Networking

Azure Virtual Network (VNet) is the fundamental building block for your private network in Azure.

Stream Analytics

Azure Stream Analytics

Microsoft Azure Stream Analytics is a serverless scalable complex event processing engine by Microsoft that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media, and other applications.

Solidity

Enterprise business intelligence

Enterprise business intelligence is the deployment of BI throughout an enterprise, usually through the combination of an enterprise data warehouse and an enterprise license to a BI platform or tool set that can be used by business users in various roles.

Testimonials

Instructors and Experts

Learn from India's Best leading faculty and industry leaders

Sanjeev

Sanjeev Singh

EXP 18+
Sameer

Sameer

EXP 15+
Satwik

Satwik Muthappa

EXP 15+
Mujaheed

Mujaheed

EXP 12+

Program Fee

Designing an Azure Data Solution (DP-201)

INR. 28,990*

Inclusive of all Taxes

No Cost EMI Available

Frequently Asked Questions

What is Azure Data Solution?

Azure Data Engineers design and implement the management, monitoring, security, and privacy of data using the full stack of Azure data services to satisfy business needs.

What is Azure Data Solution Used for?

Azure data engineers are responsible for data-related implementation tasks that include provisioning data storage services, ingesting streaming and batch data, transforming data, implementing security requirements, implementing data retention policies, identifying performance bottlenecks, and accessing external data sources.

What is a learning path?

Learning paths are collections of modules that are organized around specific roles (like developer, architect, or system admin) or technologies (like Azure Web Apps, Power BI, or Xamarin.Forms). When you finish a learning path, you've gained a new understanding of different aspects of the technology or role you're studying. You also get a trophy!

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