Outline a blueprint for the data warehouse use case by identifying individual modules, as well as their responsibilities and interactions with each other.
- Let us now start to outline a solution…for the problem we have defined.…To recap, we have our source data…that is currently stowed in an Oracle database.…Let's call this the audit database.…Currently, we only store for 15 days…but want to scale up to three years of history.…We need to create a new audit archive database…to which we will copy the audit trail data from Oracle.…This audit archive database should support the goals…we have defined for our use case.…
We will also need to build a data pump…that will periodically move data…from the audit DB to the audit archive.…The data pump should provide…for easy configuration and operation.…It should also provide the ability…to scale and do parallel data extraction…and import as the volume grows.…We want to make this architecture a blueprint…for any such projects the company wants…to execute in the future.…
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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