User Manual
5. Don’t Boil the Ocean. Finally, Intel’s Marty
Sedler advises, “We always try to go in and say
we’re going to solve the whole big problem and
it becomes so overwhelming that you never
reach the end game, the success. Break it down
into pieces where you can see progress rather
than trying to get there in one jump.”
Our research identified that organizations have
specific challenges in attaining energy and
sustainability goals. The appropriate application
of technology can help organizations attain
those goals. When evaluating solutions, our
respondents indicated that the most important
factor for success when buying a big-data
analytics solution is the ensure there is
“functionality that meets current needs.” Big-
data analytics promises to enable enhanced
decision-making and improve enterprise-level
energy management when the solution deployed
meets the organization’s needs.
14
Three Big Myths About Big Data © 2014 GreenBiz Group Inc. www.greenbiz.com.
“We’re in an exciting time for enterprise-level use of data analytics as its potential is just now starting to be realized.
The feedback we’re getting from our customers is a positive sign that we’re headed in the right direction as we’ve made
it a point of emphasis to blend industry-leading technology with our analytical expertise. It’s crucially important that
we’re able to help our customers cut through the clutter in order to find meaningful information that drives real business
results. This is easier said than done, but with the advent of advance metering technologies and data-transparency
platforms like Advantage™ Navigator from Siemens we’re confident that we can help put “big data” to work for you.”
-Dave Hopping, President, Siemens Building Technologies Americas
61%
53%
53%
42%
39%
28%
8%
8%
8%
Functionality that meets current needs
Price
Ease of use
Integration with existing equipment and software packages
Functionality that meets future plans
Assurance of data quality
Existing relationship with supplier
Brand reputation
Other
What were the top factors that were considered when
buying a big data/analytics solution?