- INFORMATION SYSTEMS IN CONSTRUCTION
- Analytical Studies of BIG Data in Construction
- UDC 004:66/67:69:72
Pavel B. KAGAN, e-mail: email@example.com
Moscow State University of Civil Engineering (National Research University), Yaroslavskoe shosse, 26, Moscow 129337, Russian Federation
Abstract. The importance and relevance of solution of issues of large information data arrays processing in construction are substantiated. The use of Big Data at the planning stage already provides the better understanding of expenditures and time limits and significant amount of data analyzed makes it possible to considerably reduce the project risks. The problem of using traditional data warehouses is the need for data cleansing and convert them to a specific format. In addition, they require the preliminary processing, introduction of dummy variables, for example, and others. Methods used when analyzing Big Data are not demanding to their type and make it possible to work with unstructured values. The article considers the issues of applicability of the concept of Big Data at various stages of the life cycle of a construction object. The special importance of the use of tasks of the intellectual data analysis in combination with technologies of information simulation of buildings is emphasized. An approach in which the analysis of data of arbitrary type can be reduced to the analysis of text similar to conventional text messages is presented. At the moment, it is of interest to identify and fix non-obvious dependencies present in the analyzed data. It is shown that the advantage of using Big Data is that it is not necessary to put forward hypotheses for verification in advance, since they appear in the process of data analysis. The concept of a fully automated Big Data analysis system is proposed.
Key words: Big Data, Data Mining, information simulation in construction, data management.
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- For citation: Kagan P. B. Analytical Studies of Big Data in Construction. Promyshlennoe i grazhdanskoe stroitel'stvo [Industrial and Civil Engineering], 2018, no. 3, pp. 80-84.