Module 1: Data Platform Architecture Considerations
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
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Module 2: Azure Batch Processing Reference Architectures
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
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Module 3: Azure Real-Time Reference Architectures
Lessons
- 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
The student will learn about the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.
Lessons
- Introducing QnA Maker
- Implement a Knowledge Base with QnA Maker
- Integrate QnA with a Bot
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Module 4: Data Platform Security Design Considerations
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
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Module 5: Designing for Resiliency and Scale
Lessons
- 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
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
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Module 6: Design for Efficiency and Operations
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
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