Big data analytics

Big data analytics

Analysing a very large volume of diverse data to reveal patterns. In construction, big data from previous projects can be used to improve project planning, and big data from facility management systems can be used to optimise the operation of the built environment.

Big data is characterized as a large volume of data, which has a large variety and large velocity in the sense that new data is constantly produced. Big data can originate from a number of sources, e.g. social media updates, sensors in wearables, sensors installed in the built environment and credit card transactions.

Big data is analysed to extract behaviour patterns, e.g. to understand historic events or to predict the future behavior of a system. Here we describe how big data is used to analyse the current situation and reveal patterns. Prediction is handled as a separate technology (artificial intelligence prediction).

Since data can be of any kind, big data analytics can be used for many purposes. In construction, big data analytics might be used for:

  • Improving project planning and budgeting, as this to a larger extend can be based on historic knowledge from previous, similar projects.
  • Make the site work more efficient, e.g. by tracking tools and materials on the construction site and understanding how to reorganize things to streamline work processes.
  • Optimise the operation of the built environment e.g. saving energy as installed sensors report usage patterns

Benefits and challenges

Big data analytics

  • can provide information to aid decision making processes in construction, hereby likely improving time, cost and quality of construction projects.
  • data collection sources need to be selected with care to avoid biased results.
  • may compromise the privacy of individuals if not treated with proper care.
  • leveraging data from multiple data sources in a meaningful way is challenging

Application example

The global concrete construction company, Dayton, has used big data analytics to make their pricing of materials more transparent and consistent to customers. Big data analytics helped the sales representatives take lots of factors into account when deciding on a price of building materials, including local availability, market conditions, and customer expectations (www.cio.com).

Development stage

The technology has been demonstrated, although not fully implemented in the construction sector.

Construction impact

Big data analytics can affect work in all phases of a construction project.

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