Course DP-201T01-A: Designing an Azure Data Solution

Microsoft

Course DP-201T01-A: Designing an Azure Data Solution

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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, 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.

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.

Prerequisites

Course outline

Module 1: Data Platform Architecture Considerations

Module Overview

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 Sessions

Case Study

Lab Lessons

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.

Module 2: Azure Batch Processing Reference Architectures

Module Overview

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 Sessions

Architect an Enterprise-grade Conversational Bot in Azure

Lab Lessons

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.

Module 3: Azure Real-Time Reference Architectures

Module Overview

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 Sessions

Azure Real-Time Reference Architectures

Lab Lessons

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.

Module 4: Data Platform Security Design Considerations

Module Overview

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 Sessions

Data Platform Security Design Considerations

Lab Lessons

Defense in Depth Security Approach
Identity Protection

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

Module Overview

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 Sessions

Designing for Resiliency and Scale

Lab Lessons

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.

Module 6: Design for Efficiency and Operations

Module Overview

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 Sessions

Design for Efficiency and Operations

Lab Lessons

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.

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