Learn about some key design issues and recommendations for the individual components within the customer analytics use case.
- [Instructor] In this section, we will solely focus on…how we can make our rest APIs, scalable, and efficient.…We first look at the best practices for rest API design.…Avoid the temptation to create too may queries.…Normalize queries, such that there are…individual queries, for most used scenarios,…but general catch all queries, for less used ones.…Keep the queries generic, and use case driven.…
Focus on what the user needs, not what he wants.…Document your REST API clearly, so that the consumers,…do not struggle with their usage.…A good documentation prevents additional support work,…your developers have to do later.…Finally, conform to the REST API best practices,…we will discuss in the next video.…Let us now focus on how to build your APIs,…for best performance.…First, paginate results.…
This means, when the user executes a query,…you only provide the first hundred or so, records.…If the user needs more, they will requery,…asking for records,…that starts from where the earlier query ended.…This keeps the pay load for each request small,…
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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