Analyze the problem statement for the customer analytics use case, and set out the goals to achieve while architecting the solution.
- [Instructor] We now get to the final use case…in this course, Customer Analytics.…This use case extends the earlier use case we saw…about customer 360.…The earlier use case focused on building the customer 360.…This use case focuses…on enabling analysts and data scientists…to use the data store we built.…Let us look at the problem we have to solve.…Analysts need explorative analytics capability…on the data store we created.…
This means they should be able to slice and dice data…as they wish to perform the analysis they desire.…They need a tool to build flexible visualizations…and reports.…You have your e-commerce application…that needs real-time access to the customer summary.…When the customer visits your website,…you should be able to use this information…to enable custom browsing and, also, to provide deals…for the customer.…
Other applications in your business need access…to the customer transaction data.…Data scientists in your business needs…to pull out transaction data…for doing their model building and predictive analytics.…
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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