Chapter 8. Putting It All Together

Where do you go from here?

Try reexamining your goals for different projects and see what advantages you might gain from transitioning to a universal stream-based approach in addition to the specific benefits for your real-time analytics applications.

The fact is, there’s a revolution in what you can do with streaming data for a wide variety of use cases, from IoT sensor data to financial services, telecommunications, web-based business, retail, healthcare, and more. New technologies that efficiently handle continuous event data with speed at scale are part of why this revolution is possible. Another key ingredient is a new way to design architecture that exploits these emerging technologies. The big change is to see the power in a universal stream-based design. This does not mean that streaming data is used for everything, but it does mean that streaming becomes a common approach rather than something considered only for specialized, real-time projects.


There are great benefits to be gained when stream-based designs for big data architectures become a habit.

At the heart of effective stream-based architecture is the message passing itself. A big difference between stream-based and traditional design (or even people’s preconception of streaming) is that the messaging layer plays a much more prominent role. It can and should be used for more than just a step to precede real-time analytics, although it is essential for processing streaming ...

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