Finesse the earlier architecture blueprint for the Customer 360 use case with technology options and finer details to arrive at the final architecture
- [Instructor] Let us now finish the solution…with the technology decisions we made…in the earlier video.…We will use Apache Spark for building the eCommerce pipe…that would move data from eCommerce system…to the processing module.…We will use Apache Kafka for the order processing pipe.…We will again use Apache Kafka for the support pipe.…Given that Apache Kafka supports multiple topics…on the same instance,…we can use one instance of an Apache Kafka cluster…with each of these application systems…publishing their data as separate topics onto the cluster.…
We will use Apache Spark for performing…the standardization and summarization tasks.…Apache Kafka in this case will work…as a batch processing engine.…It will wake up at regular intervals,…read pending messages from the topics,…process them, and store them in the 360 degree database.…Finally, for the database,…we have determined in the earlier video…that we would be splitting them…as summary and interactions databases.…
We will use Cassandra for the summary database.…
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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