دانلود گزارش تجزیه و تحلیل داده های بزرگ و سیستم های هوشمند – برای هوش تهدید سایبری

We are living in the dawn of what has been termed as the “Fourth Industrial Revolution” by the World Economic Forum (WEF) in 2016. The Fourth Industrial Revolution is marked through the emergence of “cyber-physical systems” where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT). Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This new area of technology has been defined as Big Data Science and Analytics, and the industrial and academic communities are realizing this as a competitive technology that can generate significant new wealth and opportunity. Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. In the recent years, there has been an exponential growth in the both structured and unstructured data generated by information technology, industrial, healthcare, retail, web, and other systems. Big data science and analytics deals with collection, storage, processing and analysis of massive-scale data on cloud-based computing systems. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. There are very few books that can serve as a foundational textbook for colleges looking to create new educational programs in these areas of big data science and analytics. Existing books are primarily focused on the business side of analytics, or describing vendor-specific offerings for certain types of analytics applications, or implementation of certain analytics algorithms in specialized languages, such as R.