Название: Challenges and Applications of Data Analytics in Social PerspectivesАвтор: V. Sathiyamoorthi, Atilla Elci
Издательство: IGI Global
Год: 2021
Страниц: 340
Язык: английский
Формат: pdf (true)
Размер: 12.0 MB
With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress.
Big data, machine learning and business analytics concepts are trending topics in today’s businesses. There have been much discussions going on these topics but there is also a need to explain these concepts. The large data volume does not classify it as just the big data age, because there have always been larger volumes of data than we can effectively work with. What separates the present as the big data age is the change in the behavior of companies, governments and non-profit organizations. During this period, they want to start using all the data they can collect to improve their business for an unknown purpose, present or future. Big Data sources which make big data ‘big’ are sensors, digitizers, scanners, digital modeling, mobile phones, the Internet, videos, emails and social networks. Data types flowing from these sources in a very large and diverse range include text, geometries, images, videos, sounds and a combination of each. such data can be directly or indirectly converted into purpose-oriented business information.
The irresistible charm of processing big data requires understanding and application in other very important concepts, which is where the real competitive advantage goes. ‘Machine Learning’ is a key concept to use the big data in order to boost your enterprise’s marketing and other business operations’ performance. The term ‘machine learning’ is often, incorrectly, interchanged with Artificial Intelligence, but machine learning is a sub field/type of Artificial intelligence. Machine learning is also often referred to as predictive analytics, or predictive modelling.
Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.
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