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Designing the Lambda Architecture and Real-time Processing


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
The importance of data processing architectures and data visualization to successfully implement real-time big data analytics solutions in Azure cannot be overstated. This course covers the Lambda architecture and Azure Stream Analytics.

Target Audience
Professionals who are preparing to take the 70-475: Designing and Implementing Big Data Analytics Solutions certification exam, and who are experienced in designing, programming, implementing, automating, and monitoring Microsoft Azure cloud platform solutions. Exam candidates should also be adept at using development tools, techniques, and design methodologies associated with the implementations of cloud-based big data analytics solutions.

Prerequisites
None

Expected Duration (hours)
1.8

Lesson Objectives

Designing the Lambda Architecture and Real-time Processing

  • start the course
  • recognize what the Lambda architecture is and how it is used
  • list considerations for the Lambda batch layer design
  • identify considerations for the Lambda serving layer design
  • list considerations for the Lambda speed layer design
  • recognize the key capabilities and limitations of the Lambda architecture
  • recognize the difference between Lambda and Kappa architectures
  • recognize traditional data analytics approaches and how they differ from streaming solutions
  • recognize how value is generated through real-time data analytics solutions
  • identify how Azure Stream Analytics work
  • recognize the benefits and capabilities of Azure Stream analytics
  • compare Apache Storm and Azure Stream Analytics
  • recognize the Azure architecture and the various components of data sources, integration, and real-time analytics
  • recognize the Azure output storage and consumption components
  • design reference data streams from Blob Storage
  • design and configure stream reference data from Event Hubs and IoT source
  • store and view Stream Analytics jobs
  • visualize big data with Power Pivot
  • visualize big data with Power View
  • create custom reports with SQL Server Reporting Services
  • recognize the features of the Lambda architecture and the capabilities of Azure Stream
  • Course Number:
    df_dibd_a04_it_enus

    Expertise Level
    Intermediate