Outline a blueprint for the Customer Analytics use case by identifying individual modules, as well as their responsibilities and interactions with each other.
- [Instructor] Let us now outline the solution…for our Customer Analytics use case.…We have a customer 360 database…that we built in our previous use case.…We did split them physically yearly here…into Cassandra and Elasticsearch.…But we will deal with that split when we get…to the actual architecture for this use case.…We add a visualization tool to this database…that can provide explorative analytics capability.…
This tool should provide good visualization capabilities…like graphs and dashboards.…It should allow the users to design their own reports…with little or no programming.…It is acceptable for this tool…to only work with the customer transaction details…and not the customer summary.…This is because we can build a summary…from the transactions when needed.…We add a Rest API to this data stored also.…The Rest API provides programmatic access…to other applications and data scientists to pull data…out of the data store to perform their required analytics.…
Let us now delve deeper into how the Rest API…that people would look like.…
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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