Cleantech Market Intelligence
The Fog of Big Data
Big Data and the analytics to extract useful information from it have great potential for smart buildings technology. As these terms are used more broadly, though, they risk losing their original meanings. For many people, Big Data means “a lot of data” and analytics is diluted to mean “processing a lot of data.” These general usages risk blurring the real opportunities afforded by Big Data and analytics in the smart buildings sector.
This was reinforced at two June vendor conferences I participated in: Realcomm’s IBcon conference in Orlando and Schneider Electric’s Xperience Efficiency event in Washington D.C. Schneider marketing director Kent Evan’s trends presentation at Xperience Efficiency cited the early definition of big data, as described by META Group (now Gartner) analyst Doug Laney in a 2001 research report. That is, Big Data has three attributes: volume, velocity, and variety. But Evans reminded the audience that not every data problem in buildings is a Big Data problem – there’s plenty of work we need to do to make better use of the small data we have available to us.
While I generally agree with this assessment, it is still worth reviewing how smart building data volume, velocity, and variety are challenging traditional building management systems. Certainly, data volume is growing as building control systems with hundreds of control points morph into complex systems with many thousands of points, driven by more granular sensors and controls. The velocity of this data is also increasing as sensors are sampled more frequently and denser submetering deployments provide more information to systems operations. The variety of the data is growing as well, especially as different systems – ranging from HVAC to lighting to security (including video) – become data sources for an increasing range of potential applications. Building data may not suffer from as many structured versus unstructured data challenges as experienced in other industries, but existing applications are often straining to process this data. More importantly, new types of processing offer new insights and control optimizations.
This processing issue gets to the second part of my concern about the imprecision of the term “analytics.” There were dozens of software vendors at the IBcon conference hawking buildings analytics packages, and on the surface, the marketing messages blur the distinction between them. At the risk of oversimplification, these packages can be sorted into two buckets: those that use complex rules to effectively sort through lots of data to discover the desired information, and those that algorithmically fuse disparate data sets together to infer new actionable information and insights. Products in both buckets can perform impressive and useful tasks, but the latter is the class of applications that are best described as true analytics.
Perhaps the best advice for building operators trying to sort through the Big Data and analytics hype is to focus on the specific problems at hand and understand how the proposed solutions offered arrive at their answers. Whether they involve Big Data or little data, analytics or advanced rules engines, solving problems is the ultimate goal.