The increase in networking of building systems in the last decades has made large quantities of data available to building operators and facility managers. It has also confronted them with a new challenge: how to use the data to improve their building's performance.
The volume of data for a large building makes its analysis complex and time-consuming. Highly efficient performance of a building requires data from a large number of sources. The sources can be inside a building (equipment, spaces, lighting), outside (weather), or other factors such as utility rates. Gathering the data can mostly be automated, but using it to make operational decisions is a challenge.
Cimetrics' decision to develop and offer the Analytika service was based upon many years' experience in working with building operators and understanding their problems. Facility managers are busy people, and performance analysis is not necessarily a priority. We recognized that for the service to be really effective it should not only include all the relevant analyses, but also include specific recommendations for improving performance.
So from its inception a major goal of the project was development of tools that aid analysts in quickly and efficiently analyzing a building's performance, and developing a prioritized list of improvement actions.
It's also worth noting that the Analytika project mostly predated the Internet of Things. When it began, the amount of data, while quite large, was smaller than now because its sources were more limited. As the IoT has evolved and the number of data sources grown, it has been possible to extend our analytics experience to other fields, notably Industrial IoT and biochemical processes. We are now actively investigating areas where our experience in analytics can be applied to add value to large scale data gathering.
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