Review the technology options available for the customer analytics use case, compare them, and choose the right one for the modules.
- [Instructor] Let us now look at the technology options…we have for the customer analytics use case.…Let us first look at the visualization tool we need.…There are a number of commercial visualization tools…available that can work on multiple databases…and provide the users with great visualization capabilities.…Given that it's commercial,…I choose to not recommend a specific tool,…rather you can use the same selection principle…we used in the earlier use cases…to select a tool for your organization.…
In this use case, however, I would recommend using Kibana.…Kibana is built by the same vendors as Elasticsearch…and has excellent integration with Elasticsearch itself.…It should be sufficient…for providing the capabilities we need for this use case.…We then get into considering technologies…for our REST APIs.…REST APIs need to provide custom,…business-specific and use-case specific interfaces.…
Out-of-the-box products today…do not provide this capability.…There might be some that can come out in the future though.…
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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