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Our lives are now completely surrounded by massive amounts of data. Over the past 20 years, data have significantly expanded on a large scale in various dimensions. The concept of big data was originally introduced in the early 1880s when the world first realized there was an issue with excessive data, and following that, the data keeps growing at an unforeseen rate (Foote, 2017). The first use of the phrase big data was initiated by John R. Mashey in the 1990s (Enterprise Big Data Framework, 2019). Since then, with the developed platform, big data has addressed the issue of excessive data.
According to Foote (2017) supported by Zulkefli et. al. (2018), big data is a collection of structured, semi-structured, and unstructured data that businesses have gathered for use in predictive modeling, machine learning, and other advanced analytics applications. Moreover, big data is now a new technology generation that aims to make it possible for businesses and professionals to profitably extract value from huge, diverse, and dynamic data characteristics (Darrell, 2012; Abdullah et. al., 2022; Jaafar et. al., 2022). In addition, big data will become a significant market element, supporting growing waves of productivity growth and innovation, as long as the necessary policies and enablers are in place (Bilal et. al., 2016; Ali et. al., 2019; Samiya, 2020).
In general, the adoption of big data creates a data-driven decision-making arena, allowing organizations to make informed decisions and reduce response time. Big data technology, in particular, increases an organization’s competitive advantage by optimizing business operations and transcending customer value (Bilal et. al., 2016; Zulkefli et. al., 2018; Jaafar et. al., 2022). Thus, these potentials, when combined, have a significant impact on productivity improvement.
Complex event processing, big data streaming, and highly high-speed, large-scale analysis of massive heterogeneous datasets are just a few of the capabilities available in today’s big data technologies (Bilal et. al., 2016; Peiffer, 2016; Wolfert et. al., 2017; Ali et. al., 2019; Jamaluddin; 2022). Due to quickly evolving technology, the amount of data in the world today has continually expanded. This can be proof that at the moment, businesses handle petabytes (1015 bytes) of data.
For example, Google processes around 24 petabytes of data each day, meanwhile, Facebook receives over 10 million photographs every hour. In addition, the data excess increased by roughly 2.5 quintillion (1018) bytes per day in 2012. Thus, researchers have numerous prospects to acquire crucial insights and knowledge as a result of this data accumulation. However, it is debatable whether the availability of data will enhance or even replace current statistical and computational methods to improve the status quo in various disciplines (Bilal et. al., 2016; Samiya, 2020; Aziz et. al., 2023).
Among the uses of big data for the construction industry, the highest adoption is performance prediction (Bilal et al., 2016). It can facilitate the project manager to evaluate the potential issues for a construction project. In the fourth industrial revolution, big data contributed to the construction industry for technology support (Atuahene et al., 2020). It positively affected the construction industry, making it more efficient and effective.
However, though the construction industry has applied big data to the industry, the application of big data in the construction industry is still in the infancy level. In the initial stage, the professionals applied big data to forecast the success of the project (Narayan and Tan, 2019). In particular, the professionals applied big data to support the Neural Networks (NN) for the purpose of forecasting (Katarina et al., 2015).
Thus, the result of the application is accurate as the forecast of the project. In a nutshell, big data can bring industries to a higher standard. The widespread digital revolution is not an exception in the construction industry. In the context of the construction industry, technology investment is viewed as a driver of productivity, economic growth, and increased contribution to the Gross Domestic Product (GDP).
The construction industry has to deal with sizeable data from various disciplines. Nowadays, the amount of data produced by the construction industry has grown tremendously due to the ongoing use of modern technologies. Thus, data growth resulted in a significant data phenomenon expected to transform the construction industry completely. Big data, which is a transformational paradigm like other technologies, will inevitably have an impact on the construction industry.
With the industry’s continued focus on increased efficiency, big data’s values make it intriguing to embrace. Despite hesitations, the construction industry is on the verge of a technological revolution that will shape its future.
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