Review the technology options available for the customer 360 use case, compare them, and choose the right one for the modules.
- [Instructor] We will now try to identify technologies…that would fit into our solution outline.…Let us choose a technology that will be used…to store our Customer360 summary…and interactions.…We will start off with the goals for this technology.…The data store should provide elastic scalability.…It should scale horizontally as the number of customers…and interactions grow over time.…It should provide excellent query performance…to support ad hoc queries by realtime systems.…
The customer summary record will be updated heavily…by the processing module,…as more and more data for the customer is generated,…hence the data store should also provide…excellent update performance.…The data store should have flexible schema or no schema,…so adding new attributes to the records should be easy…and should not involve significant development…or database administration resources.…The interaction details record can be expected…to be filtered by any attribute in the record,…hence it should provide fast filtering…by any column in the record.…
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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