Abstract
The paper studies the processing of large information data arrays (Big Data) in construction. The issues of the applicability of the big data concept (Big Data) at various stages of the life cycle of buildings and structures are considered. Methods for data conversion for their further processing are proposed. The methods used in the analysis of "big data" allow working with unstructured data sets (Data Mining). An approach is considered, in which the analysis of arbitrary data can be reduced to text analysis, similar to the analysis of ordinary text messages. At the moment, it is important and interesting to isolate non-obvious links present in the analysed data. The advantage of using big data is that it is not necessary to advance hypotheses for testing. Hypotheses appear during data analysis. Dependence analysis is a basic approach when working with big data. The concept of an automatic big data analysis system is proposed. For data mining, text analysis algorithms should be used, and discriminant functions should be used for the main problem to be solved (data classification).
Highlights
In recent years, firms, companies, enterprises, public services, etc. due to its activities, a considerable amount of data, sometimes heterogeneous and unstructured, has been accumulated, on different types of media, with different storage methods, etc
Traditional ways of processing information presented in the form of relational databases are not able to work with unstructured data, such as free text or data coming from analog sensors
Over the past few decades, research has been conducted on the development of methods for the detection and diagnosis of faults and the application of knowledge about construction sites to improve maintenance during operation
Summary
Firms, companies, enterprises, public services, etc. due to its activities, a considerable amount of data, sometimes heterogeneous and unstructured, has been accumulated, on different types of media, with different storage methods, etc. The approaches associated with processing, storing and analyzing large amounts of data have become quite widespread Such a direction, connected with the change of data processing and analysis technology, with the development of distributed data storage and processing systems, with the departure from traditional bases and banks, was given the general name Big Data [1, 2]. Traditional ways of processing information presented in the form of relational databases are not able to work with unstructured data, such as free text or data coming from analog sensors. Another important concept in this area was the term Data Mining (“intelligent” or “in-depth” data analysis), that is, a set of methods for detecting previously unknown, nontrivial, but useful and accessible knowledge in large data arrays. Another important concept in this area was the term Data Mining (“intelligent” or “in-depth” data analysis), that is, a set of methods for detecting previously unknown, nontrivial, but useful and accessible knowledge in large data arrays. for decision making in various areas of human activity
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