000			03281nam a2200457 i 4500
001			11007926
003			CaPaEBR
005			20240726104619.0
008			150126s2015 nyu foab 001 0 eng d
020			_a9781631571213
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050	0	4	_aHF _b.B875 2015
100	1		_aMaheshwari, Anil, _d1949-, _e1
245	1	0	_aBusiness intelligence and data mining /Anil K. Maheshwari.
250			_aFirst edition.
260			_aNew York, New York (222 East 46th Street, New York, NY 10017) : _bBusiness Expert Press, _c(c)2015.
300			_a1 online resource (xiv, 162 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,
505	0	0	_a1. Wholeness of business intelligence and data mining -- _t2. Business intelligence concepts and applications -- _t3. Data warehousing -- _t4. Data mining -- _t5. Decision trees -- _t6. Regression -- _t7. Artificial neural networks -- _t8. Cluster analysis -- _t9. Association rule mining -- _t10. Text mining -- _t11. Web mining -- _t12. Big data -- _t13. Data modeling primer -- _tAdditional resources -- _tIndex.
520	3		_aBusiness is the act of doing something productive to serve someone's needs, and thus earn a living, and make the world a better place. Business activities are recorded on paper or using electronic media, and then these records become data. There is more data from customers' responses and on the industry as a whole. All this data can be analyzed and mined using special tools and techniques to generate patterns and intelligence, which reflect how the business is functioning. These ideas can then be fed back into the business so that it can evolve to become more effective and efficient in serving customer needs. And the cycle continues on. Business intelligence includes tools and techniques for data gathering, analysis, and visualization for helping with executive decision making in any industry. Data mining includes statistical and machine-learning techniques to build decision-making models from raw data. Data mining techniques covered in this book include decision trees, regression, artificial neural networks, cluster analysis, and many more. Text mining, web mining, and big data are also covered in an easy way. A primer on data modeling is included for those uninitiated in this topic.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat reader.
588			_aTitle from PDF title page (viewed on January 26, 2015).
650		0	_aBusiness information services.
650		0	_aData mining.
650		0	_aBusiness intelligence.
653			_aData Analytics
653			_aData Mining
653			_aBusiness Intelligence
653			_aDecision Trees
653			_aRegression
653			_aNeural Networks
653			_aCluster analysis
653			_aAssociation rules
856	4	1	_uhttps://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000349.html _zClick here to access this RESOURCE ONLINE | Login using your my.ciu username & password
942			_m2015 _c1 _hHF. _i2021-2022 _dCynthia Snell
999			_c72799 _d72799
902			_a1 _bCynthia Snell _c1 _dCynthia Snell