# Development of Cost and Schedule Data Integration Algorithm Based on Big Data Technology
## 1 Introduction  
At present, we are living in a big data era. As the information age proceeds, there has been a large increase in demand and dependence on information to achieve data-driven insights in decision-making [1]. In the construction industry, the significance of data and its latent value also become greater to enhance project management. There have been various efforts to systematically manage information in construction projects by introducing information management systems, such as continuous acquisition and life-cycle support (CALS), project management information system (PMIS), enterprise resource planning (ERP), and building information modeling (BIM). These systems, however, have contributed to a relatively low improvement of efficiency rate over recent decades; data management is still trying to catch up with the exponential data growth in this sector.  
Data in construction management has characteristics with a vast amount, various formats, complicated structure, and frequent changes as projects proceed [2]. The magnitude and complexity of gathered data are continuously growing as projects progress. It leads to challenges in standardization and generalization of data utilization.  
In construction projects, data management is still under a paper document-oriented process, which results in (1) loss of critical construction management data after project completion, (2) lack of available and meaningful data, and (3) absence of database for knowledge share in future projects. Developing a methodology for processing and analyzing construction project data that reflects datacharacteristics is essential for innovation in this industry. This paper aims to propose a data processing algorithm for construction management, which extracts and analyzes the required data by various stakeholders from a wide range of data sources associated with construction projects.  
Construction project management is a series of systematic procedures to manage the design, cost, schedule, quality, and safety. Cost and schedule management are regarded as project success factors [3]; data associated with them is not only used for cost and schedule control but also management of productivity, labor, periodic payment, and material of construction projects. Based on its connectivity and importance, existing studies highlight the integration of cost and schedule data as an effective solution for effective project management [4]. However, there has been a lack of applicable models in practice due to the issues inherent in the vast, dynamic, and complex nature of data. As fundamental data for construction management, the proposed algorithm in this research focuses on integrating cost and schedule data management; it involves quantity, cost, schedule, and payment, which are intertwined with each other, from the database perspective.  
To achieve this aim, this paper proceeds as follows. First, the related works and concepts related to the integration of cost-schedule data are discussed in Section 2. In Section 3, characteristics and challenges in cost-schedule data integration are identified, and the feasibility of big data technology is examined as solutions for the challenges. Based on the previous study [4], Section 4 addresses the development of an algorithm for integrating cost and schedule management that consists of a multi-dimensional and -level data structure and seven modules incorporating big data technology. Lastly, Section 5 present a case study of the implemented algorithm to analyze its validity from three perspectives: data integrity and flexibility, data building and transformation time, and practicability.