Learn about use cases and best practices for architecting batch mode applications using big data technologies such as Hive and Apache Spark.
- [Kumaran] Hi, my name is Kumaran Ponnambalam. Welcome to my course about architecting batch mode big data applications. The course focuses on architecting big data applications. It reviews the unique challenges of building big data applications. It then looks at five real-life use cases for batch mode big data applications. In each use case, we show you how to analyze the problem, draw an outline architecture, choose technologies, finish the architecture, and review some best practices.
The course is generally intended for big data engineers, architects, and developers. We'll discuss a number of big data technologies in this course, so students are expected to have some prior familiarity with these technologies. Being an architecture course, there is no coding involved. 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 data acquisition, transport, processing, storage, and service. 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: archiving audit logs and performing customer analytics
- Technology options
- Designing solutions
- Best practices
Skill Level Advanced
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
1. Intro to Big Data Applications
2. Use Case 1: Data Warehouse (DW)
3. Use Case 2: Log Accumulation (LA)
4. Use Case 3: IT Operations Analytics (OA)
5. Use Case 4: Customer 360 (C360)
6. Use Case 5: Customer Analytics (CA)
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