000			04192nam a2200745 i 4500
001			11252268
003			CaPaEBR
005			20241023114847.0
006			m eo d
007			cr cn |||m|||a
008			160914s2016 nyu foa 001 0 eng d
020			_a9781631575617 _qe-book
035			_a(BEP)4659276
035			_a(OCoLC)958391029
035			_a(CaBNVSL)swl00406814
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aQA76.9.B45
100	1		_aPark, Patrick H., _eauthor.
245	1	0	_aBig data war : _bhow to survive global big data competition / _cPatrick H. Park.
250			_aFirst edition.
264		1	_aNew York, New York (222 East 46th Street, New York, NY 10017) : _bBusiness Expert Press, _c[(c)2016.]
300			_a1 online resource (x, 195 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_adata file _2rda
490	1		_aBig data and business analytics collection, _x2333-6757
500			_aIncludes index.
505	0		_aPart 1. Dump the data -- _t1. Global data war -- _t2. Why did Google TV fail? -- _t3. Why do they analyze data? -- _tPart 2. Data is human -- _t4. Think as a customer -- _t5. Big data, start from human -- _t6. Why does Nike compete with Nintendo? -- _tPart 3. Data is created by me -- _t7. Knowing necessary data is everything in data analytics -- _t8. Create data -- _tPart 4. We don't need the past -- _t9. Predict human unconsciousness -- _t10. Anything with a pattern can be predicted -- _tPart 5. What matters at the end is performance -- _t11. Data is strategy -- _t12. Big data, a long way to go -- _tEpilogue -- _tAbout the author -- _tIndex.
506			_aAccess restricted to authorized users and institutions.
520	3		_aWritten by Patrick H. Park, an author of Brain Work (Korea, 2014). The book mainly focuses on why data analytics fails in business. It provides an objective analysis and root causes of the phenomenon, instead of abstract criticism of utility of data analytics. The author, then, explains in detail on how companies can survive and win the global big data competition, based on actual cases of companies. Having established the execution and performance-oriented big data methodology based on over 10 years of experience in the field as an authority in big data strategy, the author identifies core principles of data analytics using case analysis of failures and successes of actual companies. Moreover, he endeavors to share with readers the principles regarding how innovative global companies became successful through utilization of big data. This book is a quintessential big data analytics, in which the author's know-how from direct and indirect experiences is condensed. How do we survive at this big data war in which Facebook in SNS, Amazon in e-commerce, and Google in search expand their platforms to other areas based on their respective distinct markets? The answer can be found in this book.
530			_a2 _ub
530			_aAlso available in printing.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat reader.
588			_aTitle from PDF title page (viewed on September 14, 2016).
650		0	_aBig data.
650		0	_aQuantitative research.
653			_aAmazon
653			_aApple
653			_abig data
653			_abusiness intelligence
653			_aconsulting
653			_acustomer analysis
653			_acustomer profiling
653			_aCRM
653			_adata
653			_adeep learning
653			_aFacebook
653			_aGoogle
653			_aIT
653			_amachine learning
653			_aMBA
653			_amarketing
653			_aproduct profiling
653			_aproblem solving
653			_astrategy
653			_aTech
653			_aVenture
655		0	_a[genre]
776	0	8	_iPrint version: _z9781631575600
830		0	_aBig data and business analytics collection. _x2333-6757
856	4	0	_uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000515.html
942			_2lcc _bCIU _cOB _eBEP _QOL _zBEP11252268
999			_c72763 _d72763
902			_c1 _dCynthia Snell