• Online, Self-Paced
Course 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.

Learning Objectives

The Lambda Architecture

  • 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

Real-time Analytics Processing Solutions

  • 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

Big Data Visualization Tools

  • visualize big data with Power Pivot
  • visualize big data with Power View
  • create custom reports with SQL Server Reporting Services

Practice: Real-time Analytics Processing

  • recognize the features of the Lambda architecture and the capabilities of Azure Stream

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.