Showing results for "Information Technology" in Data Science

In "Information vs Data" Ira Warren Whiteside redefines how we perceive and utilize information and data in today's technological environment. This book integrates advanced concepts of artificial intelligence (AI) and business intelligence (BI) to demonstrate their impact on modern industries.

Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of big data. Listeners are guided through tried-and-true methodologies for getting more out of data and using it to the utmost advantage. This audiobook describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding big data, all while guiding listeners toward better decision-making from the perspective of a data scientist.

"Big Data" is on the covers of Science, Nature, The Economist, and Wired magazines, on the front pages of the Wall Street Journal and The New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure.

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?