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Architecting Big Data Applications: Real-Time Application Engineering

via LinkedIn Learning

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Details

This course may be unavailable.

Provider

LinkedIn Learning
Pricing

Free Trial Available
Languages

English
Certificate

Certificate Available
Duration & workload

1-2 hours
Sessions

Finished

Found in

Part of

Become a Data Engineer: Mastering the Concepts

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Overview

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

Syllabus

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

Taught by

Kumaran Ponnambalam

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