Course Outline

Module 1: Streaming Overview

  • Key differences between batch and streaming
  • Streaming Data Management use cases
  • Streaming architecture 
  • Kappa architecture
  • End-to-end Streaming Data Management
  • Types of Streaming data
  • Benefits of Streaming

Module 2: Edge Data Streaming (EDS) Overview

  • EDS architecture
  • EDS key features
  • EDS Data flow process
  • EDS UI
  • Create an EDS Service
  • Create a data flow
  • Deploy a data flow
  • Monitor the data flow
  • Lab1: Create Edge Data Streaming Service
  • Lab2: Create and Deploy a Data Flow

Module 3: Big Data Streaming Overview

  • Big Data Streaming overview
  • Stream Data Processing with Spark streaming
  • BDS component architecture
  • BDS key features

Module 4: Kafka Overview

  • Kafka Concepts
  • Kafka core APIs
  • Topics in Kafka
  • Kafka models
  • Kafka Use cases
  • Lab: Create a Kafka connection

Module 5: Streaming Mappings

  • Sources in a Streaming Mapping
  • Targets in Streaming Mapping
  • Lookup sources
  • Kafka Data Object Properties
  • Lab: Create a Mapping with Kafka Source and HDFS Target
  • Lab: Create a Mapping with Kafka Source and Kafka Target
  • BDS Transformations
  • Lab: Enhance Mapping Using Filter and Expression Transformations
  • Lab: Enhance Mapping Using Window and Aggregator Transformations
  • Lab: Enhance Mapping Using Sorter and Rank Transformations

Module 6: Monitoring Logs and Troubleshooting

  • Spark Monitoring
  • Viewing Logs
  • Troubleshooting
  • Lab: Monitor an EDS Data Flow
  • Lab: Monitor a BDS Mapping

Module 7: Performance Tuning and Best Practices

  • Tune performance of Spark jobs
  • List some best practices while working with streaming data

Module 8: End-to-End Use Case

  • Use Case
  • EDS and BDS – Final Goal
  • Lab: Convert Unstructured Streaming Data into Structured Data
  • Lab: Ingest Data from EDS to BDS and Execute a Mapping in BDS


  14 Hours


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