Real-time processing is an important part of your Hadoop architecture, but is it always the best approach to data-driven applications? The reality is that there are a host of situations where real-time not only costs your business unnecessary time and effort, but can also produce erroneous results. Join the experts from MapR and ThinkBig as they delve into the decision making process around Hadoop real-time and batch processes. You will learn the ins and outs of low-latency design for analytics, as well as see how these designs get implemented in the real world.
This one hour webinar is offered by Data Science Central, and is recommended for anyone working with Hadoop. Key takeaways include:
- Useful design patterns for building your Hadoop stack that best serves low-latency requirements
- Pitfalls to avoid when choosing your real-time processing option – sometimes batch is the right solution
- Real customer examples highlighting the decision-making process for both real-time and batch processing