Published since 1923
DOI: 10.33622/0869-7019
Russian Science Citation Index (RSCI) íà ïëàòôîðìå Web of Science
  • INFORMATION SYSTEMS IN CONSTRUCTION
  • Analytical Studies of BIG Data in Construction
  • UDC 004:66/67:69:72
    Pavel B. KAGAN, e-mail: kagan@mgsu.ru
    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.
  • REFERENCES
    1. Forman D. Mnogo tsifr: analiz bol'shikh dannykh pri pomoshchi Excel [Many numbers: analyze big data using Excel]. Moscow, Al'pina Pablisher, 2016. 464 p. (In Russian).
    2. Prokopets A. Konkurentnoe programmirovanie na Scala [Competitive programming on Scala]. Moscow, DMK-Press Publ., 2018. 342 p. (In Russian).
    3. Vikent'eva O. L., Deryabin A. I., Shestakova L. V., Kychkin A. V. Synthesis of information management system of subsystems of technical support of intellectual buildings. Vestnik MGSU, 2017, vol. 12, iss. 10 (109), pp. 1191-1201. (In Russian).
    4. Konikov A. I., Konikov G. A. Study of Interrelationship of objectives, methods and resources for marketing of construction projects. Promyshlennoe i grazhdanskoe stroitel'stvo, 2017, no. 10, pp. 78-82. (In Russian).
    5. Ginzburg A. V. Building life cycle information modelling. Promyshlennoe i grazhdanskoe stroitel'stvo, 2016, no. 9, pp. 61-65. (In Russian).
    6. Kagan P. B. Modeling of the development areas. Vestnik KIGIT, 2012, no. 12-3, p. 9. (In Russian).
    7. Kagan P. B. Presentation of Information in design, construction and operation of linear objects of engineering communication networks. Promyshlennoe i grazhdanskoe stroitel'stvo, 2016, no. 3, pp. 71-75. (In Russian).
    8. Kagan P. B., Polyakov R. G. The use of genetic algorithms for solving problems of technological equipment in construction. Nauchnoe obozrenie, 2017, no. 10, pp. 15-19.(In Russian).
    9. Ignatov V. P., Ignatova E. V. Management decision-making in fuzzy conditions. Vestnik MGSU, 2009, no. 4, pp. 332-335. (In Russian).
    10. Lezerson U., Riza S. Spark dlya professionalov. Sovremennye patterny obrabotki bol'shikh dannykh [Spark for professionals. Modern patterns of big data processing]. St. Petersburg, izdatel'skiy dom "Piter" Publ., 2017. 272 p. (In Russian).
  • 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.


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