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

 

Module 1

Data Platform Architecture Considerations

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

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

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

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


Module 5

Designing for Resiliency and Scale

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

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