| Issue |
E3S Web Conf.
Volume 535, 2024
XIII International Scientific and Practical Forum “Environmental Aspects of Sustainability of Construction and Management of Urban Real Estate” (ESCM-2024)
|
|
|---|---|---|
| Article Number | 05011 | |
| Number of page(s) | 8 | |
| Section | Innovative, Technical and Information Systems of “Smart City” | |
| DOI | https://doi.org/10.1051/e3sconf/202453505011 | |
| Published online | 11 June 2024 | |
Using AI and big data in decision making: A framework across disciplines
1 Moscow State University of Civil Engineering ; Yaroslavskoe shosse, 26, Moscow, 129337, Russia
2 TISBI University of Management, 11/43 Mushtari st, Kazan, Republic of Tatarstan, Russia
3 Global humanistic university, Anguilla
* Corresponding author: GrabovyiyPG@mgsu.ru
The recent growth in computer architecture has changed the face of education, science and engineering. Technology does not stand still, and today, when assessing the economic development of the organization, university or industry, the attention is paid to its willingness to use new technologies, especially in the field of Artificial Intelligence (AI) and big data analytics. In this research, the topic of AI and Big Data and its integration into decision-making process for competitiveness is examined. The emergence of Big Data and related analytics technologies led to changes in the business world. In today’s business processes, extracting genuine value form AI and Big Data, and integrating it into the core decision-making strategy plays a vital role. In this paper the necessary steps for the successful integration of AI and Big Data and analytics are covered, by analyzing the success factors from literature. Finally, its implications in real estate market and education are discussed with a small-scale cases analysis.
Key words: Artificial Intelligence / Big Data / Big Data analytics / big data technology decision-making / firm readiness / education / value-creation / success factors / interactive decision support / analysis methods / real estate
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.