Join Kumaran Ponnambalam for an in-depth discussion in this video Next steps, part of Architecting Big Data Applications: Real-Time Application Engineering.
- [Kumaran] There is a lot more to understand…with real-time big data architecture.…The information can extend…well beyond this course.…I have a couple of recommendations…for you if you wish to keep practicing.…First, implement some of the use cases you learnt…and experience how the solution works.…Try architecting similar solutions…for some of your own use cases.…Learn more about the technologies…we discussed in this course.…
Data always intrigues me.…I bet it intrigues you too,…so let's keep exploring it and find better ways to move it…and extract knowledge out of it.…
There is no coding involved. Instead you will see how big data tools can help solve some of the most complex challenges for businesses that generate, store, and analyze large amounts of data. The use cases are drawn from a variety of industries, including ecommerce and IT. Instructor Kumaran Ponnambalam shows how to analyze a problem, draw an architectural outline, choose the right technologies, and finalize the solution. After each use case, he reviews related best practices for real-time streaming, predictive analytics, parallel processing, and pipeline management. Each lesson is rich in practical techniques and insights from a developer who has experienced the benefits and shortcomings of these technologies firsthand.
- Components of a big data application
- Big data app development strategies
- Use cases: fraud detection and product recommendations
- Technology options
- Designing solutions
- Best practices
Skill Level Advanced
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
1. Real-Time Big Data
2. Use Case 1: Social Media Sentiment Analysis (SM)
3. Use Case 2: Real-Time Fraud Detection (FD)
4. Use Case 3: Website Production Recommendations (PR)
5. Use Case 4: Mobile Couponing (MC)
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