Big data? It’s a phrase that you hear bandied about in the information-technologies sector, and it is trumpeting its way into the mechanical systems trades in the form of fault detection and building analytics. Big data describes large, complex sets of data that, if interpreted properly, can provide insight into how a building is actually performing from an energy standpoint.

Modern buildings are full of data-collection systems—from building management, which captures temperature and humidity levels, to access control, which collects occupancy statistics, to other measurements too.

In a blog on Greenbiz.com, Sudhi Sinha, Snehil Taparia, and Swarup Biswas, explain that the traditional approach to energy-baseline definition is to correlate whole-building consumption with outside-air temperature, occupancy, and level of operations.

However, the authors say that with advanced metering and building automation systems, data broken down into many variables can create a large volume of data to analyze. This allows for more targeted analysis, but also means we need to identify the most important variables for analysis.

In July 2013, a report from an organization called IMS Research, was issued. It concludes that the market for fault detection based on big-data building analytics will expand at a compound annual growth rate of more than 40 percent during the next five years.

What does this mean to building owners and managers? Everything. The idea behind such analytics is saving energy and increasing their bottom line.

And you can help. Check out Ken Elovitz’s article, “Analyzing Building Energy Use.”  Elovitz provides a methodology for using historical energy-use and weather data to understand energy consumption in commercial buildings.

“He writes: “The first step in most HVAC design projects is to calculate heating and cooling loads. These calculations become the basis for sizing equipment and, when required, projecting energy use.”

He advocates for facilities and consulting engineers to become more adept at utility-bill analysis as a tool  to understand HVAC energy use and find ways to use energy in buildings more effectively.

We also have a case study on Page 26 that depicts a project where everything was done “right,” but something went wrong. In his article,”Building Measurement & Analytics,” Charles Rechtsteiner of Autodesk Inc. discusses lessons learned from the design and construction of a new headquarters building.

He says, “We used advanced design and energy-analysis tools, followed protocols, and installed advanced and efficient equipment, and still found equipment-sequencing issues, communication conflicts, incorrect measurement, and higher-than-expected resource consumption.”

He goes on to describe how through the use of new and advanced building analytics tools, Autodesk discovered where the problems originated and made corrections that resulted in a 16-percent resource reduction over a three-year period.

The fact is, smart buildings, the smart grid, and smart HVAC technology is the evolution in the buildings market. Big data is the result. Are you ready to be in the analysis game? You should—it is our future.