Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Lapina, Maria; Kulikova, Svetlana; Kireenkov, Vadim; Kumar, Sandeep Title A name given to the resource Development of a Comprehensive Technology for Analyzing Data on the Used Car Market Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1122;pp.503-514 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-97-7426-5_38" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-7426-5_38</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85218197731?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218197731?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lapina M., Department of Information Security of Automated Systems, North-Caucasus Federal University, Stavropol, Russian Federation; Kulikova S., Department of Applied Informatics, Moscow Polytechnic University, Moscow, Russian Federation; Kireenkov V., Department of Applied Informatics, Moscow Polytechnic University, Moscow, Russian Federation; Kumar S., CHRIST (Deemed to be University), Kengeri Campus, Bengaluru, 560074, India Description An account of the resource In today's information society, organizations face a huge amount of data that requires analysis and intelligent technologies to make informed decisions. In this paper, the authors consider the problem of analyzing the used car market using big and open data technologies. The used car market has characteristics characterized by heterogeneity and dynamic demand depending on the region. This problem is relevant and important not only for companies involved in producing and selling cars but also for potential buyers. The authors developed a comprehensive data analysis technique based on the Python programming language and the K-means clustering algorithm in the research process. In the article, the authors described a comprehensive technology for analyzing the used car market, including various analysis methods, such as prices, offers, and competition. The proposed comprehensive technology includes various tools and programs for collecting, processing, and analyzing data. These methods can be combined into a single system, providing a more complete picture of the market and making more informed decisions. The structure of the study reflects an independent approach to the topic under study based on open data and research by Russian and foreign scientists. It should be noted that the study is based on a large amount of analytical data obtained from reliable sources and tools that confirm the conclusions formulated in this study. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Data mining; K-means; Power BI; Processing technology; Region analysis Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981977425-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online