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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
Testimonials (1)
Sufficient hands on, trainer is knowledgable