Architecting Big Data Applications: Real-Time Application Engineering

Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.

Introduction

• Welcome

1. Real-Time Big Data

• What is real time?
• Real-time challenges
• Strategies for real-time big data processing

2. Use Case 1: Social Media Sentiment Analysis (SM)

• 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

3. Use Case 2: Real-Time Fraud Detection (FD)

• FD: Analyze the problem
• FD: Outline the solution
• FD: Consider technologies
• FD: Lay out the architecture
• FD: Design key elements
• Best practices: Predictive analytics

4. Use Case 3: Website Production Recommendations (PR)

• PR: Analyze the problem
• PR: Outline the solution
• PR: Consider technologies
• PR: Lay out the architecture
• PR: Design key elements
• Best practices: Parallel processing

5. Use Case 4: Mobile Couponing (MC)

• MC: Analyze the problem
• MC: Outline the solution
• MC: Consider technologies
• MC: Lay out the architecture
• MC: Design key elements
• Best practices: Pipeline management

Conclusion

• Next steps