000			01913cam a2200301 i 4500
003			MIUC
005			20190924102554.0
008			190924s2018 nyua 001 0 eng
020			_a9781292220543
020			_a1292220546
040			_aDLC _beng _cDLC _erda _dDLC _dMIUC
042			_apcc
082	0	0	_a658.472
100	1		_aSharda, Ramesh _92199
240	1	0	_aBusiness intelligence
245	1	0	_aBusiness intelligence, analytics, and data science : _ba managerial perspective / _cRamesh Sharda, Dursun Delen, Efraim Turban ; with contributions to previous editions by J. E. Aronson, Ting-Peng Liang, David King.
250			_aFourth edition, global edition.
260			_aNew York : _bPearson, _c[2018].
300			_axxvi, 486 p. : _bill. col. _c26 cm.
504			_aIncludes bibliographical references and index.
505	0		_aCh. 1. An Overview of Business Intelligence, Analytics, and Data Science -- Ch. 2. Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization -- Ch. 3. Descriptive Analytics II: Business Intelligence and Data Warehousing -- Ch. 4. Predictive Analytics I: Data Mining Process, Methods, and Algorithms -- Ch. 5. Predictive Analytics II: Text, Web, and Social Media -- Ch. 6 Prescriptive Analytics: Optimization and Simulation -- Ch. 7. Big Data Concepts and Tools -- Ch. 8. Future Trends, Privacy and Managerial Considerations in Analytics.
520			_aFor courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems.To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.
650		0	_aBusiness intelligence _92200
650		0	_aIndustrial management _949
700	1		_aDelen, Dursun _4aut _92201
700	1		_aTurban, Efraim _4aut _9664
942			_2ddc _cBK