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Learn about real-time analytics through real-world examples

December 16, 2013

Whether you call it stream computing, data in motion or real-time data, there’s no doubt that one of the most important aspects of big data is being able to capture, process and analyze data as it is happening. This is the velocity component of anybody’s definition of big data.

Unlike data that’s stored in an enterprise data warehouse (EDW) and analyzed at some later time, real-time data is processed the instant it flows, or streams, into the system. The obvious benefit of this is faster reaction times. For example, the short video below tells how one telecommunications company cut the time needed to analyze data from 12 hours to just one minute! This gave them the ability to make on-the-fly network adjustments to handle spikes in usage.

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Of course, we’re all happy when that all-important text message (“Big cup of hot coffee & a tasty donut on my day off. Ahhh! #notmissingwork LOL!”) goes through when we hit send. But how else might real-time data be useful?

How about to re-route vehicles to avoid accidents or traffic congestion? That’s what smarter cities like Stockholm, Sweden and Brisbane, Australia are doing. Read more about these uses in “Travel and Transportation in the Age of Big Data” and “Next Best Action on the Streets of Your Town.”

Real-time data can help save lives, too, as these two blog posts illustrate:

  • Saving Lives at 1,000 Data Points Per Second” tells how UCLA is developing a bedside early-warning system that measures intracranial pressure in patients with traumatic brain injuries. When the pressure becomes threateningly high, the system immediately alerts caregivers. Previously, this was a manual process that might happen only once per hour—or even longer. Such a delay could be lethal.
  • The Fusion of Big Data and Little Babies” is one of my favorite stories. Doctors and Researchers at Toronto’s SickKids Hospital used InfoSphere Streams to capture and analyze real-time data flowing from monitors on newborn babies. With this active monitoring, they were able to predict, and treat, dangerous infections 24 hours earlier than previous methods.

There are so many uses for real-time data (such as in predictive maintenance to replace parts before a catastrophic failure or to enable an efficient electric smart grid) it’s no wonder that Ventana Research presented IBM's real-time analytics product InfoSphere Streams with the IT Innovation Award for Operational Intelligence.

To learn more about how “data in motion” can be harnessed, watch the excellent overview video below or visit this page for other blog posts, podcasts and resources on real-time data. Finally, if you want to dive in and experiment yourself, you can download the InfoSphere Streams QuickStart Edition at no cost and try it out.

How might you use real-time data? Add a comment below with your ideas.