Big Data: A Very Short Introduction (Very Short Introductions)
| Author | : | |
| Rating | : | 4.97 (764 Votes) |
| Asin | : | 0198779577 |
| Format Type | : | paperback |
| Number of Pages | : | 144 Pages |
| Publish Date | : | 2013-08-14 |
| Language | : | English |
DESCRIPTION:
Dawn Holmes is a faculty member in the Department of Statistics and Applied Probability at the University of California, Santa Barbara, specializing in Bayesian networks, machine learning, and data mining. She is the co-editor of a three-volume work, Data Mining: Foundations and
It includes all our uploaded documents, video, and photos, all our social media traffic, our online shopping, even the GPS data from our cars."Big Data" represents a qualitative change, not simply a quantitative one. These pocket-sized books are the perfect way to get ahead in a new subject quickly. At the same time, it raises important ethical issues; Holmes discusses cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers. Big data is transforming the way businesses operate, and the way medical research can be carried out. Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Holmes uses a variety of case studies to explain how data is stored, analyzed, and exploited by a variety of bodies from big companies to organizations concerned with disease control. Dawn E. Once access to the Internet became a reality for large swathes of the world's population, the amount of data generated each day became huge, and continues to grow exponentially. The term refers both to the new techno
She is the co-editor of a three-volume work, Data Mining: Foundations and IntelligentParadigms (Springer, 2014), and Associate Editor of the International Journal of Knowledge-Based and Intelligent Information Systems.. About the AuthorDawn Holmes is a faculty member in the Department of Statistics and Applied Probability at the University of California, Santa Barbara, specializing in Bayesian networks, machine learning, and data mining