DP-201T01: Designing An Azure Data Solution Associate

Course overview

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.

Course Duration

2 Days

Cost

Audience

  • 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

  • DP-200T01: Implementing an Azure Data Solution Associate (Data Engineer)
  • AZ-900T01: Microsoft Azure Fundamentals (1 Day)

Course Content

Data Platform Architecture Considerations

  1. Core Principles of Creating Architectures
  2. Design with Security in Mind
  3. Performance and Scalability
  4. Design for availability and recoverability
  5. Design for efficiency and operations
  6. Case Study

Lab : Case Study

  1. Design with security in mind
  2. Consider performance and scalability
  3. Design for availability and recoverability
  4. Design for efficiency and operations

Azure Batch Processing Reference Architectures

  1. Lambda architectures from a Batch Mode Perspective
  2. Design an Enterprise BI solution in Azure
  3. Automate enterprise BI solutions in Azure
  4. Architect an Enterprise-grade Conversational Bot in Azure

Lab : Architect an Enterprise-grade Conversational Bot in Azure

  1. Designing an Enterprise BI solution in Azure
  2. Automate an Enterprise BI solution in Azure
  3. Automate an Enterprise BI solution in Azure

Azure Real-Time Reference Architectures

  1. Lambda architectures for a Real-Time Perspective
  2. Architect a stream processing pipeline with Azure Stream Analytics
  3. Design a stream processing pipeline with Azure Databricks
  4. Create an Azure IoT reference architecture
  5. Lab : Azure Real-Time Reference Architectures
    1. Architect a stream processing pipeline with Azure Stream Analytics
    2. Design a stream processing pipeline with Azure Databricks
    3. Create an Azure IoT reference architecture

Data Platform Security Design Considerations

  1. Defense in Depth Security Approach
  2. Identity Management
  3. Infrastructure Protection
  4. Encryption Usage
  5. Network Level Protection
  6. Application Security

Lab : Data Platform Security Design Considerations

  1. Defense in Depth Security Approach
  2. Identity Protection

Designing for Resiliency and Scale

  1. Adjust Workload Capacity by Scaling
  2. Optimize Network Performance
  3. Design for Optimized Storage and Database Performance
  4. Identifying Performance Bottlenecks
  5. Design a Highly Available Solution
  6. Incorporate Disaster Recovery into Architectures
  7. Design Backup and Restore strategies

Lab : Designing for Resiliency and Scale

  1. Adjust Workload Capacity by Scaling
  2. Design for Optimized Storage and Database Performance
  3. Design a Highly Available Solution
  4. Incorporate Disaster Recovery into Architectures

Design for Efficiency and Operations

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

Lab : Design for Efficiency and Operations

  1. Maximize the Efficiency of your Cloud Environment
  2. Use Monitoring and Analytics to Gain Operational Insights
  3. Use Automation to Reduce Effort and Error

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