El big data, entendido como la gestión y el almacenamiento masivo de datos, es una tendencia por explotar a día de hoy. La industria audiovisual, consciente de ello, empieza a orientar estrategias de negocio con ideas de personalización de contenidos, segmentación de perfiles o predicción de tendencias. Comprender todas las posibilidades que nos ofrece el big data supone entender las dinámicas internas del negocio, así como las fuentes de datos de las que podemos extraer información y la interacción que podemos realizar con ellas. Y también nos permite formular mejores preguntas y tomar decisiones acertadas. Este libro ofrece un recorrido por el proceso de gestión de datos en la empresa, con introducción de explicaciones técnicas y especial atención a la toma de decisiones del business intelligence.

This book constitutes the proceedings of the 5th International Conference on Applied Informatics, ICAI 2022, which took place in Arequipa, Peru, in October 2022. The 32 papers presented in this volume were carefully reviewed and selected from 90 submissions. The contributions are divided into the following thematic blocks: Artificial Intelligence; Data Analysis; Decision Systems; Health Care Information Systems; ICT-Enabled Social Innovation; Image Processing; Robotic Autonomy; Software Architectures; Software Design Engineering.

​This volume provides an overview of the ways sustainable development issues as a whole, and the SDGs in particular, are perceived and practiced in a variety of countries in the Latin America and Caribbean region. It also discusses the extent to which its many socio-economic problems hinder progresses towards the pursuit of a sustainable future, and documents successful experiences from across the region. This book is part of the "100 papers to accelerate the implementation of the UN Sustainable Development Goals initiative".

This book gathers selected papers presented at the Inventive Communication and Computational Technologies Conference (ICICCT 2022), held on May 12–13, 2022, at Gnanamani College of Technology, Tamil Nadu, India. The book covers the topics such as Internet of Things, social networks, mobile communications, big data analytics, bio-inspired computing, and cloud computing. The book is exclusively intended for academics and practitioners working to resolve practical issues in this area.

Las organizaciones han usado estrategias, como la inteligencia de negocio, para tomar mejores decisiones a partir de los datos. Actualmente, en la era de los datos, nuestros clientes son más inteligentes, están más informados y ya no son tan leales con nuestra marca. Esperan experiencias inolvidables y profundamente personalizadas en cada una de las interacciones con nuestra organización. Como resultado, las organizaciones están obligadas a transformar sus estrategias para conocer mejor las necesidades y preferencias de sus clientes, basándose en una enorme cantidad de datos.

In the digital transformation era, integrating business intelligence and data analytics has become critical for the growth and sustainability of industrial organizations. However, with this technological evolution comes the pressing need for robust cybersecurity measures to safeguard valuable business intelligence from security threats. Strengthening Industrial Cybersecurity to Protect Business Intelligence delves into the theoretical foundations and empirical studies surrounding the intersection of business intelligence and cybersecurity within various industrial domains. This book addresses the importance of cybersecurity controls in mitigating financial losses and reputational damage caused by cyber-attacks. The content spans a spectrum of topics, including advances in business intelligence, the role of artificial intelligence in various business applications, and the integration of intelligent systems across industry 5.0. Ideal for academics in information systems, cybersecurity, and organizational science, as well as government officials and organizations, this book serves as a vital resource for understanding the intricate relationship between business intelligence and cybersecurity. It is equally beneficial for students seeking insights into the security implications of digital transformation processes for achieving business continuity.

This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations. Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.