Outline a blueprint for the operations analytics use case by identifying individual modules, as well as their responsibilities and interactions with each other.
- [Instructor] Let us now embark…on outlining the solution for our…IT operations analytics use case.…Let us first review the data sources we have.…First, we have the audit trail data in Hive.…To identify performance bottlenecks,…we are specifically interested in the user…operation performed, timestamp when it was performed…and the webserver in which it happened.…We also have the performance logs in Hive.…
To identify performance bottlenecks,…we are interested in the CPU load,…memory load and Disk I/O on specific webservers…at different times.…We need to process and integrate this data…and create a destination table…that contains the following information…regarding a five-minute window.…Recall that a given day is split…into five-minute window, we then…have the specific webserver ID and the performance…characteristics for that webserver…in that five-minute window.…
We also have a specific user operation…like viewer reviews and the percentage…of times this operation happened…in a specific five-minute window…on the specific web server.…
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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