Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
Overview
Syllabus
Introduction
- Welcome
- What is real time?
- Real-time challenges
- Strategies for real-time big data processing
- SM: Analyze the problem
- SM: Outline the solution
- SM: Consider technologies
- SM: Lay out the architecture
- SM: Design key elements
- Best practices: Real-time streaming
- FD: Analyze the problem
- FD: Outline the solution
- FD: Consider technologies
- FD: Lay out the architecture
- FD: Design key elements
- Best practices: Predictive analytics
- PR: Analyze the problem
- PR: Outline the solution
- PR: Consider technologies
- PR: Lay out the architecture
- PR: Design key elements
- Best practices: Parallel processing
- MC: Analyze the problem
- MC: Outline the solution
- MC: Consider technologies
- MC: Lay out the architecture
- MC: Design key elements
- Best practices: Pipeline management
- Next steps
Taught by
Kumaran Ponnambalam