Issue |
MATEC Web Conf.
Volume 251, 2018
VI International Scientific Conference “Integration, Partnership and Innovation in Construction Science and Education” (IPICSE-2018)
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Article Number | 03062 | |
Number of page(s) | 7 | |
Section | Engineering and Smart Systems in Construction | |
DOI | https://doi.org/10.1051/matecconf/201825103062 | |
Published online | 14 December 2018 |
Research of the possibilities of application of the Data Warehouse in the construction area
Moscow State University of Civil Engineering, Yaroslavskoye Shosse 26, Moscow, 129337, Russia
* Corresponding author: a.konikov@gmail.com
Today, in information technologies, the direction associated with the use of Data Warehouse (DW) is evolving very dynamically. Using DW, it is possible to implement two types of data analysis: OLAP-analysis: a set of technologies for the rapid processing of data presented as a multidimensional cube; Data Mining is an intelligent, deep analysis of data to detect previously unknown, practically useful patterns (in our case, the construction area). It is noted, that of all the methods used in technology Data Mining, cluster analysis is especially useful for the construction area. At present, the role of DW has increased, significantly due to the fact, that many methods and approaches of Data Mining have formed the basis of a new, promising method of Big Data. We will specify that, that Data processing from the Data Warehouse with the help of technology Big Data, allows to deduce researches in a building area to the higher level. The purpose of this work is to research of the possibilities of application of the Data Warehouse in the construction area. The article suggests the new approach to data analysis in the construction area, based on the use of Big Data technology and elements of OLAP - analysis. In the section “Discussion” is considering the possibility of the new promising business in the construction field, based on the application of Data Warehouse and technology Big Data.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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