Exam DP-201

Designing an Azure Data Solution


About this course
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.

Audience profile
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.



Languages: English
Audiences: Data Professional
Technology: Azure Data Platform
Length: 2 days

 
 

or contact us

Mamoni Tanti
Project Manager
+91 72900 11333
esi@technofocus.co

 

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.

Core Principles of Creating Architectures
Design with Security in Mind
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.

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.

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


Module 4

Data Platform Security Design Considerations

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

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, 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.

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.

Maximizing the Efficiency of your Cloud Environment
Use Monitoring and Analytics to Gain Operational Insights
Use Automation to Reduce Effort and Error