000			02872cam a2200325 i 4500
001			17949914
003			OSt
005			20161123115718.0
008			131121s2014 flua b 001 0 eng
010			_a 2013045992
020			_a9781466596092 (hardback)
040			_aDLC _beng _erda _cDLC
042			_apcc
050	0	0	_aHD38.7 _b.B865 2014
082	0	0	_a658.472 _223 _bBUA
084			_aBUS042000 _aCOM021030 _aCOM032000 _2bisacsh
245	0	0	_aBusiness analytics : _ban introduction / _ceditor, Jay Liebowitz.
300			_axi, 276 pages : _billustrations ; _c24 cm
504			_aIncludes bibliographical references and index.
520			_a"Preface It is plain and simple: Big Data and business analytics are hot! Whether the cover of the October 2012 Harvard Business Review, the December 2012 MIT conference on "Big Data: The Management Revolution," or the January 2013 issue of KMWorld, these emerging areas will continue to gain ground with great momentum in the coming years. According to a Cisco study, as mentioned in the January 2013 KMWorld issue, Kapil Baskhi (Chief Architect, Cisco Public Sector) states that global IP traffic will reach 1.3 zettabytes annually by 2016, which is a fourfold increase from 2011. By 2016, there will be 19 billion global network connections, the equivalent of two-and-a-half connections for every person on earth. According to Dan Vesset, Program VP for Business Analytics Solutions at IDC (in the same KMWorld issue), the Big Data market is expected to reach $16.9 billion by 2015, up from $3.2 billion in 2010. Steve Lohr's December 30, 2012 New York Times article headline indicates, "Sure, Big Data Is Great--But So Is Intuition." The point here is that with all this data coming in at various volumes, velocities, and varieties, how can we make sense of it all, especially for improving decision-making capabilities in organizations? This is where the field of business analytics can add value. Think about cybersecurity, finance, marketing, healthcare, education, energy, and many other sectors--all of these fields could benefit from applying and improving their analytics. Better detection of fraud through visual analytics and better prediction of the likelihood of someone getting an infection while in the hospital are interesting examples where analytics play a role"--
650		0	_aBusiness intelligence. _956676
650		0	_aBig data. _956677
650		7	_aBUSINESS & ECONOMICS / Management Science. _2bisacsh _956678
650		7	_aCOMPUTERS / Database Management / Data Mining. _2bisacsh _936348
650		7	_aCOMPUTERS / Information Technology. _2bisacsh _936424
700	1		_aLiebowitz, Jay, _d1957- _eeditor of compilation. _956679
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBOOK
999			_c39807 _d274307