Learn about the strategy that follows for architecting big data applications in this course.
- [Instructor] When you are architecting…a big data application,…there are specific areas that you need to address.…First, there is Business logic…that applies to a specific use case…you are trying to solve.…This is specific to your business,…and only you know what needs to be achieved.…Sometimes the use case is general,…like Social Media Analytics,…where there are off-the-shelves solutions,…but most likely your use case…will be unique to your business,…and it is better to build a custom solution.…
Besides Business logic,…there are five general requirements…for any big data architecture.…Capability, Scalability, Reliability,…Security, and Flexibility.…This is where the off-the-shelf big data products…and technologies help.…As an Architect,…you not only need to solve the business problem,…but you will need to also deliver the solution…using minimal time and resources.…
So building a big data platform completely from scratch…is not a good idea,…unless there is no product in the market…that could address your need.…The best general strategy…
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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