Simply put, “big data” is a term which refers to large or complex data sets of information that need processing and managed by analytical tools. This data can originate from a diversity of sources, such as cameras, sensors, and log files.

Perhaps a good example of big data being processed is by what can be considered the largest project in the world producing masses of data, the CERN project in Europe. Collecting enormous amounts of data produced by the particle collider, this information is automatically collated and sorted by advanced analytics software and artificial intelligence, syphoning off relevant and “important” information to be analysed by human scientists. Without the use of data analytics, it would be impossible to analyse all this data by humans alone.

Big data in construction

Big data is now being used by the construction industry to maximise efficiency and productivity. With the use of data analytic software tools, large amounts of information can be sorted and extracted from data repositories and made easily accessible to all those that need it, like contractors, architects, engineers, clients, and investors. This can help stop data wastage, like the reported approximate 96% of construction and engineering data that went unused in 2018.

Organising and budgeting

Analytics tools can be useful to construction teams by compiling data from previous and present construction projects and helping them anticipate potential delays as well as conceptualise the project timeline. The data can also be analysed to predict costs for things like materials and equipment hire, factoring in materials price increases like we have seen during the pandemic. This will help project managers better manage costs and prevent them from going over budgetary constraints; it will also help avoid any unanticipated extra costs. 

Design process

The construction industry is increasingly using digital tools like building information modelling (BIM). This allows for real time information and 3-D modelling so that all members of the team can access and input recommendations or changes, something that requires big data to be able to achieve this. Along with the use of AI, these digital tools require big data input to work. These advanced digital models are used as a predictive tool to flag up any potential issues before the construction work on the ground commences, potentially saving time and money. Moreover, any changes made can be relayed to all stakeholders in real time.

Construction work

Project management software is increasingly being used by construction workers to help analyse the mass of data and make better decisions. Once the data is analysed, it can produce automatic alerts sent to team members on potential issues and make necessary changes to schedules, which are then passed for assessment and collaboration. Team members can input data such as recommendations or ideas that can be accessed in real time by all those on the collaborative network.

As well as improving productivity and reducing costs, this software can potentially spot talent in the team as they are given free access to voice their ideas and opinions on project changes. 

Maintenance

Even after the construction phase is completed, the big data collected can be useful to the owners of the newly constructed building as this information can be used in the operation and maintenance of the building. Information gathered, for example, can help guide future renovation work and maintenance workers.
It’s possible that some builders will install and integrate sensors into the building so that things like structural conditions and temperature patterns can be permanently monitored, useful information for keeping a building well maintained and serviced.

Benefits of big data analytics

The benefits to industry from adopting big data are many and these include the following:

• Better strategic decisions

• Improved operations

• Greater customer insight

• Reducing costs

Building efficiency

Up to 35% of construction costs can be down to material waste and remedying mishaps, something that is only likely to increase with the rising costs of building materials and supply chain issues, like we are currently witnessing. With the use of data analytics, this cost can be mitigated by reducing construction time and material costs, which is achieved by early flagging of potential structural issues before labour and materials have been committed. The likelihood of human errors, therefore, can be reduced.

Environmental impact

It’s common knowledge that the construction sector holds the unenviable reputation of being a major environmental polluter. The production of cement, steel, and other materials is all energy-intensive and emits high levels of carbon. So, any reduction in the environmental impact is very welcomed.

The use of big data can help alleviate this problem by leveraging data from past projects and providing more accurate estimates of the required materials and energy for a future project. This will help mitigate wastage in materials and other precious resources. Not only will this save on wasting materials, but it will also reduce waste going to landfill sites.

Also Read: What Is Big Data? And Why Is It Important?

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