Review the technology options available for the operations analytics use case, compare them, and choose the right one for the modules.
- [Instructor] Let us now investigate the technologies…that would fit into this use case.…Recall that we are using HDFS and Hive…for storing audit data and the performance logs.…Let us now look at the technology options…for the analytics database.…If you look at the volume of data,…it is not going to be very high.…Each day have about 720 five-minute intervals.…There are 200 web servers…and about 20 unique user operations,…so we are looking at three million records a day,…small with respect to big data standards.…
So, our selection criteria…for the database technology would be the following,…we need ad hoc query capability…so that users can do any kind…of analytics they want.…We want fast response times…for interactive analytics.…The IT folks are analyzing this data…using third-party visualization products,…so we need databases that are popular…and well-supported in this regard.…
We first start with HDFS and Hive.…We are already using it,…so why not consider that…for the analytics database also?…Hive supports ad hoc query capability…
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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