Course Outline

Introduction

  • Comparison of stream processing and batch processing
  • Focus on analytics in stream processing

Overview of Frameworks and Programming Languages for Government

  • Spark Streaming (Scala)
  • Kafka Streams (Java)
  • Flink
  • Storm
  • Comparative Analysis of Features and Strengths for Each Framework

Overview of Data Sources for Government

  • Live data as a continuous series of events over time
  • Historical data sources for government operations

Deployment Options for Government

  • Cloud-based deployment (AWS, etc.)
  • On-premises deployment (private cloud, etc.)

Getting Started with Stream Processing for Government

  • Setting up the Development Environment
  • Installing and Configuring the Framework
  • Assessing Data Analysis Requirements for Government Operations

Operating a Streaming Framework for Government

  • Integrating the Streaming Framework with Big Data Tools for Government
  • Differentiating Event Stream Processing (ESP) from Complex Event Processing (CEP)
  • Transforming Input Data for Effective Analysis
  • Inspecting and Validating Output Data
  • Integrating the Stream Processing Framework with Existing Government Applications and Microservices

Troubleshooting Common Issues in Stream Processing for Government

Summary and Conclusion for Government

Requirements

  • Programming experience in any language for government applications
  • Familiarity with Big Data concepts, including Hadoop and related technologies
 21 Hours

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