Business Artificial Intelligence
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Abstract
Our entertainment and shopping media, smartphones and other devices all generate data. In 2021, just one minute on the internet accounted for 200,000 tweets, two million views on Twitch, 197 million emails and 69 million text messages, and $1.6 million in online shopping spend. This phenomenon, known as Big Data, comprises the data shared by the 3 Vs: volume, speed and variety. However, the wealth of information leads to a poverty of attention on our part, and challenges our ability to concentrate on data from different sources at the same time, which makes it necessary to set up automatic systems to process the available information. Until now, to carry out the analyses, the techniques known as Business Intelligence (BI) helped make decisions based on data analyzed by company specialists. However, these techniques currently present problems and challenges such as the analysis of structured and unstructured data, the need for predictive analysis, advanced visualizations and the lack of customization. To provide solutions to these challenges, Artificial Intelligence (AI) techniques already outperform humans when it comes to identifying trends and extracting information from complex data, capabilities that will continue to improve over time, so automation is expected of tasks in the near future that allow humans to focus on more complex decisions. In fact, these technologies have been democratized in such a way that these techniques offer knowledge in a digestible format for all users, whether they are experts or not, in uses as remarkable as predicting commercial or sales operations, providing online buyers with a personalized, optimize communication and provide real-time help to customers, manage the growing volumes of unstructured data from various sources and obtain real-time information from consumers and suppliers. The economic impact that the use of AI techniques in the field of BI can have is enormous, in addition to the continuous optimization of resources that it entails.Taking into account the promising advances of the union of both fields, the Fundació Parc Científic Universitat de València (FPCUV) puts at your disposal this monograph, coordinated by Emilio Soria Olivas, professor and founder of the Intelligent Data Analysis Laboratory (IDAL) research group at the Higher Technical School of Engineering (ETSE) of the University of Valencia, and Mariano Serra Bondia, responsible for ICT Systems at the FPCUV. Under the title Business Artificial Intelligence, the work is part of Transforma Difusión, a project that has the support of the Valencian Innovation Agency (AVI).