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Who Manages The Building Data?

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What’s the title of the person managing all your building data? Is it one person or a team from several departments? Did the team provide forethought and a strategy to all the data and information needed to manage a building? 

Have you identified all the “data "repositories" in the building, such as asset management, inventory, maintenance, building management systems, independent control systems, facility management systems, business systems, BIM data, as well as construction drawings, equipment and product data, and data in the hands of third-party contractors that install, service and maintain building equipment.

Much of the data is stored away in varied electronic and paper formats. The typical building has several "silos" of data scattered throughout the organization with no cohesive strategy for data management and little coordination. Also note that it's not only the data that is in silos but also the underlying technology systems for data management, different data management processes, and even the people involved.

There would seem to be a very good case for bringing all the facility data into a unified database architecture and putting into practice standard methodologies and processes to manage the data. There are several benefits to this approach.

The industry has realized that building data, data analytics, and even machine learning are emerging major tools for improving building operations. Data applications, such as energy management and fault detection and diagnostics, are probably the best early examples of the effectiveness of managing and analyzing data. The effort for many building owners to acquire and manage facility data, however, appears either ad hoc or narrowly focused on specific aspects of the building, such as energy and HVAC systems.

A number of data "repositories" currently used in buildings provide a substantial amount of data. They include building management systems, independent control systems, facility management systems and business systems.  In addition, there is the "umbrella" of Building Information Modeling, which addresses design and construction drawings, equipment and product data, as well as data in the hands of third-party contractors that install, service and maintain building equipment.

Some of this data is stored away in old Excel spreadsheets, Access databases and a host of varied electronic and paper formats. The typical building has several "silos" of data scattered throughout the organization with no cohesive strategy for data management and little coordination. Also note that it's not only the data that is in silos but also the underlying technology systems for data management, different data management processes, and even the people involved.

There would seem to be a very good case for bringing all the facility data into a unified database architecture and putting into practice standard methodologies and processes to manage the data. There are several benefits to this approach:

  • Building data would be more widely available and shareable: Setting aside confidential data, more data would allow for additional analytics, possibly new correlations, metrics, and insights into the building's performance.
  • Building data would be more easily accessible: Have you ever looked for as-built drawings or equipment spec sheets, only to discover that they are not where they should be? Without a structured approach to data management, you waste time internally because of the disorganization in the data and documents; many times building operators will need to contact the original architects, engineers or contractors for the data, thus wasting more time and money. What's needed is an orderly index as part of a larger data management system. A structured approach to indexing is vital as facility data grows, which is obviously very likely.
  • A structured approach can improve the archiving, preservation and retention of data for the long-term: There is some data and information that you'll want for the life cycle of the building, and there are analytic opportunities in long-term data you'll want for comparison and trending.
  • A comprehensive data management plan would improve the integrity of the data: Bad data is worthless data. You want accurate, reliable, consistent and complete data. A structured approach initially validates the data and then puts into place a process where the data can't be changed or destroyed without authorization.
  • Streamlining data: There are roughly 6,500 languages spoken in the world today; for data management, you only want one "language" of standard naming conventions, formats, indexing and data descriptors. It makes it easier to access and understand the data.
  • Improving efficiency: We don't organize data just for the sake of organizing but are doing so in order to maximize the effectiveness and efficiency of operating buildings. A structured approach can provide additional opportunities for greater correlation between data, improved data analytics and the possibility of developing or identifying new building data metrics.

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Source: automatedbuildings.com
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