DTSA 5508 Software Architecture Patterns for Big Data
- Specialization: Software Architecture for Big Data
- Instructor: Tyson Gern and Mike Barinek
- Prior knowledge needed: Software engineering or big data experience
Learning Outcomes
- Compare, measure, and test big data models for production use.
- Write custom performance tests to measure the characteristics of a distributed system.
- Use queues to horizontally distribute large workloads
- Describe pessimistic and optimistic concurrency, and identify when each can be used to solve performance issues.
Course Content
In this module, you will learn how to write tests that allow you to iterate on predictive models.
In this module, you will learn how to write performance tests to ensure your distributed system operates as expected in production.
In this module, you will learn how to use queues to horizontally distribute large workloads.
In this module, you will learn the advantages and disadvantages of high availability distributed systems.
You will complete a peer reviewed final project worth 30% of your grade. You must attempt the final in order to earn a grade in the course. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.
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