Learn about use cases and best practices for architecting real-time applications using big data technologies, such as Hazelcast and Apache Spark.
- [Instructor] My name is Kumaran Ponnambalam. Welcome to my course about architecting real-time big data applications. The course focuses on architecting real-time big data applications. First, I will review the unique challenges of building these real-time-applications. Then, I will show you four real-live use cases for real-time big data applications. In each use case, you will see how to analyze a problem, draw an outline architecture, choose technologies, finish the architecture and review some best practices.
This course is generally intended for big data engineers, architects and developers. I will discuss a number of big data technologies in the course, so I expect you to have some familiarity with these technologies. There is no coding involved in this course. Please check out the architecting batch mode big data applications course by me, Kumaran Ponnambalam, before you start this course. Let's get started.
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