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DP-201T01-A: Designing an Azure Data Solution

MSDP201
2 nap
158 000 Ft + ÁFA
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A tanfolyam célja

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, NoSQL, 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.

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.

Tematika

  • 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
  • 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
    • Describe 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
    • Identify 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

Kinek ajánljuk

Előfeltételek

Successful students start this course with knowledge of cloud computing concepts and professional experience with data solutions.

Specifically:

  • Creating cloud resources in Microsoft Azure
  • Identifying use cases for big data
  • Understanding how cloud compute services can solve for common business needs

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