The Role of Big Data in the Evolution of the Engineering and Construction Market

Big Data in Engineering Project Management – The Importance and Benefits of Data Analysis in Civil Construction

In civil construction and engineering, as in other sectors, Big Data refers to the enormous amounts of information that have been stored in the past and continue to be acquired today. Big Data can come from people, computers, machines, sensors, and any other device or data-generating agent.

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The Value of Data in Engineering and Civil Construction

Artificial intelligence, the Internet of Things, and BIM. All these major technological trends have revolutionized the civil construction market and share a common background: Big Data. This is because they rely on data to generate information that brings more security, transparency, and efficiency to engineering and construction processes – from the office to the construction site.

Therefore, creating well-established processes to collect, store, and utilize data strategically in engineering and civil construction is the first step to keep up with technological trends and market transformations. Furthermore, incorporating Big Data analysis into project management is crucial to prepare companies in the civil construction sector for the future and ensure they remain competitive in the market.

Thus, it is of little use, for example, to invest in BIM platforms and artificial intelligence tools if your engineering company does not have the necessary information to make those technologies reach their full potential.

Why Can Big Data Be Useful in Civil Construction?

Civil construction is one of the main economic activities in Brazil, but it could achieve much better results if waste were reduced and productivity increased.

Common problems in the sector, such as material waste, project delays, and budget mismanagement, can be solved using technology. Data can help managers find the root of the problems and make more accurate decisions.

If done manually, analyses can be time-consuming and unproductive, but with the use of software and analytics tools, it is possible to use them intelligently.