The term “big data” is associated with one or more of the four characteristics: volume, variety, and velocity. The technologies associated with the big data has already been proven in other sectors. Internet giants like Google, Facebook, Netflix, etc. uses big data collected from their users to present advertisements, friend recommendations, and TV shows and movies relevant to the specific user. Big data is also used for insurance fraud detection, improving bus system by reducing congestion, predictive flight arrival time, weather forecast, and genomic analysis.

For the construction industry, volume and variety becomes particularly relevant. From project planning to the project close out, a lot of structured as well as unstructured data is being generated and recorded for each construction projects. Examples of those data includes daily work report, data generated from various sensors and equipment, images and videos of the construction site, etc. Without proper tool, the data has no value, but when proper tool is used along with the data, useful insights can be obtained from it. Larger the size of data, more accurate are the predictions and conclusions drawn from it. This study explores the possible applications of big data and predictive analytics in the construction industry. The early results of the study shows the possibility of using the big data and predictive analytics for the asset management, predictive maintenance, predictive schedule analysis, performance evaluation of the subcontractors for large construction companies, improving safety of the construction work zone using video or sensor data, etc. The construction industry should be prepared to collect useful internal and external data, prepare workforce, and prepare infrastructure for storing and analyzing those data using the big data technologies. This, in turn, will make it easier for the management team to make data-driven decisions.