@article{1433774,
      recid = {1433774},
      author = {Dagnino, Aldo.},
      title = {Data analytics in the era of the industrial internet of  things /},
      publisher = {Springer,},
      address = {Cham :},
      pages = {1 online resource},
      year = {2021},
      abstract = {This book presents the characteristics and benefits  industrial organizations can reap from the Industrial  Internet of Things (IIoT). These characteristics and  benefits include enhanced competitiveness, increased  proactive decision-making, improved creativity and  innovation, augmented job creation, heightened agility to  respond to continuously changing challenges, and  intensified data-driven decision making. In a  straightforward fashion, the book also helps readers  understand complex concepts that are core to IIoT  enterprises, such as Big Data, analytic architecture  platforms, machine learning (ML) and data science  algorithms, and the power of visualization to enrich the  domains experts' decision making. The book also guides the  reader on how to think about ways to define new business  paradigms that the IIoT facilitates, as well how to  increase the probability of success in managing analytic  projects that are the core engine of decision making in the  IIoT enterprise. Useful for any industry professional  interested in advanced industrial software applications,  including business managers and professionals interested in  how data analytics can help industries and to develop  innovative business solutions, as well as data and computer  scientists who wish to bridge the analytics and computer  science fields with the industrial world, and project  managers interested in managing advanced analytic  projects.},
      url = {http://library.usi.edu/record/1433774},
      doi = {https://doi.org/10.1007/978-3-030-63139-0},
}