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Course Outline

Module 1: Streaming Overview

  • Key distinctions between batch and streaming processing
  • Use cases for Streaming Data Management
  • Streaming architecture designs
  • The Kappa architecture model
  • End-to-end Streaming Data Management strategies
  • Categories of streaming data
  • Advantages of adopting streaming

Module 2: Edge Data Streaming (EDS) Overview

  • EDS architecture
  • Core features of EDS
  • The EDS Data flow process
  • Navigating the EDS User Interface
  • Creating an EDS Service
  • Constructing a data flow
  • Deploying a data flow
  • Monitoring data flow activity
  • Lab 1: Establishing an Edge Data Streaming Service
  • Lab 2: Creating and Deploying a Data Flow

Module 3: Big Data Streaming Overview

  • Introduction to Big Data Streaming
  • Processing stream data with Spark Streaming
  • BDS component architecture
  • Key features of BDS

Module 4: Kafka Overview

  • Core Kafka concepts
  • Kafka core APIs
  • Understanding Kafka topics
  • Kafka operational models
  • Practical Kafka use cases
  • Lab: Establishing a Kafka connection

Module 5: Streaming Mappings

  • Configuring sources in a Streaming Mapping
  • Configuring targets in Streaming Mapping
  • Utilizing lookup sources
  • Properties of Kafka Data Objects
  • Lab: Constructing a Mapping with a Kafka Source and HDFS Target
  • Lab: Constructing a Mapping with a Kafka Source and Kafka Target
  • BDS Transformations
  • Lab: Enhancing Mappings with Filter and Expression Transformations
  • Lab: Enhancing Mappings with Window and Aggregator Transformations
  • Lab: Enhancing Mappings with Sorter and Rank Transformations

Module 6: Monitoring Logs and Troubleshooting

  • Spark monitoring techniques
  • Accessing and viewing logs
  • Effective troubleshooting methods
  • Lab: Monitoring an EDS Data Flow
  • Lab: Monitoring a BDS Mapping

Module 7: Performance Tuning and Best Practices

  • Optimizing the performance of Spark jobs
  • Industry best practices for handling streaming data

Module 8: End-to-End Use Case

  • Scenario overview
  • Final objectives for EDS and BDS integration
  • Lab: Transforming Unstructured Streaming Data into Structured Data
  • Lab: Ingesting Data from EDS into BDS and Executing a BDS Mapping
 14 Hours

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