000			02060cam a2200277zu 4500
001			88814381
003			FRCYB88814381
005			20250107211542.0
006			m o d
007			cr un
008			250107s2013 fr | o|||||0|0|||eng d
020			_a9780124045767
035			_aFRCYB88814381
040			_aFR-PaCSA _ben _c _erda
100	1		_aBerman, Jules J
245	0	1	_aPrinciples of Big Data _bPreparing, Sharing, and Analyzing Complex Information _c['Berman, Jules J']
264		1	_bElsevier Science _c2013
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aBerman, Jules J
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88814381 _qtext/html _a
520			_aPrinciples of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. Learn general methods for specifying Big Data in a way that is understandable to humans and to computers. Avoid the pitfalls in Big Data design and analysis. Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources.
999			_c61642 _d61642