Название: Big Data Intelligence for Smart ApplicationsАвтор: Youssef Baddi, Youssef Gahi, Yassine Maleh
Издательство: Springer
Год: 2022
Страниц: 343
Язык: английский
Формат: pdf (true), epub
Размер: 38.9 MB
Today, the use of Machine Intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity. This book presents the latest advances in Big Data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through Machine Intelligence and Big Data models and techniques. This book is helpful for students and researchers as well as practitioners.
It is worth noting that technologies such as Artificial intelligence and Big Data are evolving even faster. They are rapidly growing by holding great promise for many sectors. The real revolutionary potential of these technologies mainly relies on their convergence. Big Data and Artificial Intelligence are two technologies that are inextricably linked, to the point that we can think about Big Data Intelligence. AI has become ubiquitous in many industries where intelligent programs relying on big data transform decision-making. Increased agility, smarter business processes, and better productivity are the most likely benefits of this convergence.
Big Data, which is still poorly exploited, is nevertheless the black gold of AI. Artificial Intelligence is the logical continuation of our data analysis methods and techniques, an extension of Business Intelligence, followed by Big Data and Advanced Analytics. The so-called intelligent machine needs a massive amount of data analyzed and cross-referenced to draw innovative, even creative, capabilities close to the human brain’s functioning.
Currently, Big Data is gaining wide adoption in the digital world as a new technology able to manage and support the explosive growth of data. Indeed, data is growing at a higher rate due to the variety of the data-generating adopted devices. In addition to the volume aspect, the generated data are usually unstructured, inaccurate, and incomplete, making its processing even more difficult. However, analyzing such data can provide significant benefits to businesses if the quality of data is improved. Facing the fact that value could only be extracted from high data quality, companies using data in their business management focus more on the quality aspect of the gathered data. Therefore, Big Data quality has received a lot of interest from the literature. Indeed, many researchers have attempted to address Big data quality issues by suggesting novel approaches to assess and improve Big Data quality. All these researches inspire us to review the most relevant findings and outcomes reported in this regard. Assuming that some review papers were already published for the same purpose, we believe that researchers always need an update. It is worth noting that all the published review papers are focused on a specific area of Big data quality. Therefore, this paper aims to review all the Big Data quality aspects discussed in the literature, including Big data characteristics, big data value chain, and Big Data quality dimensions and metrics. Moreover, we will discuss how the quality aspect could be employed in the different applications domains of Big Data. Thus, this review paper provides a global view of the current state of the art of the various aspects of Big Data quality and could be used to support future research.
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