How big data is transforming the construction industry

- Equipment and IT - Jan 27, 2015

Big data analytics is being adopted at a rapid rate across every industry. It enables businesses to manage and analyze vast amounts of data at ultrafast speeds, and obtain valuable insights that can improve their decision-making processes.

One of the industries that are reaping the benefits of this technology is the construction industry. Construction companies are using big data to perform a wide range of tasks, from data management to pre-construction analysis.

Here is a look at how big data is transforming the construction industry…

How Construction Companies are Leveraging Big Data Analytics

Handling Large Amounts of Data

Many construction companies need to juggle many projects at the same time, and they have to collect, produce, organize and analyze a lot of data because of these projects.

Other than creating work reports and progress reports, they also have to manage technical information on various aspects of their projects. All the unstructured data that is collected and generated can burden their databases.

Big data solutions make it possible for construction companies to process massive amounts of data at unprecedented speeds, enabling them to save substantial time and effort, and focus more on the job site instead of IT issues.

Depending on which big data tools they use, they can improve almost every data-related process, from database management to report creation.

According to an article entitled "How Big Data is Transforming the World of Finance", big data can help businesses create reports on their operations more frequently, or in real time, so that they can make well-informed decisions on a consistent basis.

Predicting Risk

In order to plan and execute projects effectively, construction companies need to be able to predict risks accurately through intelligent use of data.

By implementing big data analytics, they can gain valuable insights that enable them to improve cost certainty, identify and avoid potential problems, and find opportunities for efficiency improvements.

One example of a construction company that is using big data analytics to predict risk is Democrata.

Democrata conducts surveys to gain a better understanding of the impact of new roads, high rail links and other construction projects, and uses big data analytics to perform searches and queries on data sets to obtain insights that can lead to better and faster decision-making.

Solving Problems

The ability to solve problems quickly can contribute significantly to the successful completion of construction projects.

Liberty Building Forensics Group is a company that investigates and solves construction and design problems, and it has provided consultation on over 500 projects worldwide, including a Walt Disney project.

According to the company, forensic issues usually occur in major construction projects, and they can cause big problems, such as failure to meet deadlines, if they are not properly assessed.

In order to fix forensic issues efficiently, construction companies have to be able to collect the right data in an organized way and make the data accessible to the right people at the right time. This can be achieved through the implementation of big data solutions.

Presently, big data analytics is relatively immature in terms of functionality and robustness.

As it continues to become more advanced, it will be more widely adopted in the construction industry.

John McMalcolm is a freelance writer who writes on a wide range of subjects, from social media marketing to technology.

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Sarah Procter    Feb 22, 2016
RIB have examples of clients who from taking and enterprise approach to the way they plan their construction production have been able to reduce risk significantly. First step is to create a Masterdatabase / single source of truth. Could be via RIB iTWO 5D technology.
Patryk Tokarek    Dec 21, 2015
John, quite an interesting point in construction. Could you please give some examples or case studies of which specific data was analysed before and what was the outcome of that research?
William S.    May 28, 2015
Interesting article John...thanks!