User Manual

The IT research ﬁrm Gartner deﬁnes big data as high-volume, high-

velocity, and/or high-variety information assets that require new forms of

processing to enable enhanced decision making, insight discovery and

process optimization.

Many large factories and ofﬁce buildings generate vast amounts of data.

According to General Motors’ Global Energy Manager Al Hildreth, “We

get data about the positions of valves and dampers and other operating

information about the heating and ventilating and air conditioning systems.

It’s a lot of data, about two-and-a-half million data points a minute.” And

that accounts for only the high-volume and high-velocity data being

generated by sensors and other means of automated data collection

within an enterprise’s portfolio of building assets.

The exponential increase of data being collected will drive improvements

only if that data is put to use. That is where technology providers promote

the use of big-data analytics to sort through all the data. Big-data analytics

can be conducted with a new breed of software tools that can perform

data mining and predictive analytics.

Big-data analytics can help energy managers understand where and when

things like set points can be changed or equipment proactively repaired

or replaced. That’s just the beginning, however. A Jetsons-like future has

been promised, with self-healing buildings that respond to factors such

INTRODUCTION