Industry 4.0 is the latest technological innovation in
manufacturing with the goal to increase productivity in a flexible
and efficient manner. Changing the way in which manufacturers
operate, this revolutionary transformation is powered by various
technology advances including Big Data analytics, Internet of
Things (IoT), Artificial Intelligence (AI), and cloud computing.
Big Data analytics has been identified as one of the significant
components of Industry 4.0, as it provides valuable insights for
smart factory management. Big Data and Industry 4.0 have the
potential to reduce resource consumption and optimize processes,
thereby playing a key role in achieving sustainable development.
Big Data Applications in Industry 4.0 covers the recent
advancements that have emerged in the field of Big Data and its
applications. The book introduces the concepts and advanced tools
and technologies for representing and processing Big Data. It also
covers applications of Big Data in such domains as financial
services, education, healthcare, biomedical research, logistics,
and warehouse management. Researchers, students, scientists,
engineers, and statisticians can turn to this book to learn about
concepts, technologies, and applications that solve real-world
problems. Features An introduction to data science and the types of
data analytics methods accessible today An overview of data
integration concepts, methodologies, and solutions A general
framework of forecasting principles and applications, as well as
basic forecasting models including naive, moving average, and
exponential smoothing models A detailed roadmap of the Big Data
evolution and its related technological transformation in
computing, along with a brief description of related terminologies
The application of Industry 4.0 and Big Data in the field of
education The features, prospects, and significant role of Big Data
in the banking industry, as well as various use cases of Big Data
in banking, finance services, and insurance Implementing a Data
Lake (DL) in the cloud and the significance of a data lake in
decision making
General
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