DP-201T01 - Designing an Azure Data Solution

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
• Case Study

Lab: Case Study

• Core principles for creating architectures
• 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

• 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

• Lambda architectures from a Batch Mode Perspective
• Designing an Enterprise BI solution in Azure
• Automate an Enterprise BI solution in Azure
• Automate an Enterprise BI solution in Azure

Module 3: Azure Real-Time Reference Architectures

• Lambda architectures for a Real-Time Perspective
• Lambda architectures for a Real-Time Perspective
• Design a stream processing pipeline with Azure Databricks
• Create an Azure IoT reference architecture

Lab: Azure Real-Time Reference Architectures

• 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

• Defense in Depth Security Approach
• Network Level Protection
• Identity Protection
• Encryption Usage
• Advanced Threat Protection

Lab: Data Platform Security Design Considerations

• Defense in Depth Security Approach
• Network Level Protection
• Identity Protection
• Encryption Usage
• Advanced Threat Protection

Module 5: Designing for Resiliency and Scale

• Design Backup and Restore strategies
• Optimize Network Performance
• Design for Optimized Storage and Database Performance
• Design for Optimized Storage and Database Performance
• Incorporate Disaster Recovery into Architectures
• Design Backup and Restore strategies

Lab: Designing for Resiliency and Scale

• Adjust Workload Capacity by Scaling
• Optimize Network Performance
• Design for Optimized Storage and Database Performance
• 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

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