Analyze the problem statement for the customer 360 use case, and set out the goals to achieve while architecting the solution.
- [Instructor] In this use case,…we will work with one of the most…popular problems for big data, the customer 360.…It is challenging because it has large volumes of data…and also needs multiple sources to accumulate that data.…So, here is the the problem for you to solve.…Your business today has 12 million customers,…who use your ecommerce website to buy products.…The customer base is expected…to grow significantly in the coming years.…
There are three independent application systems…that are used today to serve these customers.…An ecommerce system for the customers…to browse products and place orders.…An order processing system to fulfill the orders…and handle logistics.…A customer support system to track issues…that customers report and their resolutions.…Your business wants to invest in social media…analytics too in the future.…
The challenge your business has today…is that there is no single 360 degree view of the customer.…Customer interactions are split between…these three systems and it is not possible…
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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