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staggering rate. The massive parallelism built into Streams enables this data
to be analyzed in real time, so that energy generators and distributors are
able to modify the capacity of their electrical grids based on the changing
demands of consumers. In addition, companies can include data on natural
systems (such as weather or water management data) in the analytics stream
to enable energy traders to predict consumption requirements and meet cli-
ent demand. This approach can deliver competitive advantages and maxi-
mize company profits.
Manufacturers want more responsive, accurate, and data-rich quality
records and quality process controls to better predict and avoid defined out-
of-tolerance events. E-science domains, such as weather prediction, detection
of transient events, and Synchrotron atomic research are other opportunities
for Streams.
From smarter grids, to text analysis, to “Who's Talking to Whom?” analy-
sis, and more, Streams use cases are nearly limitless.
Wrapping It Up
In this chapter, we introduced you to the technical underpinnings behind
Streams. We talked about all the new enhancements in Streams 3.0 that make
it more consumable than ever before. With an easier up-and-running experi-
ence, guided task completion assistants, and round-trip editing through a
rich and agile IDE, building Streams applications is easier than ever. This is
a key point, because the consumability of Big Data technologies represents a
steep learning curve for most enterprise shops. The usability enhancements
in Streams 3.0 should come as no surprise, considering the impact of the
Streams Processing Language on Streams application development in the
Version 2.0 release.
The key value proposition of Streams is the ability to get analytics to the
frontier of the business—transforming the typical forecast into a nowcast.
This is a value proposition that few are even talking about in today's Big
Data conversations, and even fewer can deliver. Streams is proven tech-
nology with multiple applications (as detailed in this chapter) that can help
transform your business to be a leader in the Big Data era, because you can
get the right answers and make better decisions faster than others in your
industry.
 
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