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Predictive analytics, data mining and big data :myths, misconceptions and methods /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predictive analytics, data mining and big data :by Steven Finlay.
其他題名:	myths, misconceptions and methods /
作者:	Finlay, Steven,
面頁冊數:	1 online resource.
標題:	Big data.
電子資源:	https://link.springer.com/book/10.1057/9781137379283
ISBN:	1137379286 (electronic bk.)

Predictive analytics, data mining and big data :myths, misconceptions and methods /
Finlay, Steven,1969-

Predictive analytics, data mining and big data :myths, misconceptions and methods /by Steven Finlay. - 1 online resource.

1. Introduction -- 2. Using Predictive Models -- 3. Analytics, Organization and Culture -- 4. The Value of Data -- 5. Ethics and Legislation -- 6. Types of Predictive Models -- 7. The Predictive Analytics Process -- 8. How to Build a Predictive Model -- 9. Text Mining and Social Network Analysis -- 10. Hardware, Software and All That Jazz.

"Predictive analytics, big data, and data mining are key topics for organizations who want to leverage the ever increasing amounts of data that organizations hold about their customers and other individuals. This in-depth guide provides readers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, the pitfalls and dangers, and a contextual road map for developing solutions that deliver benefits to their organizations. Written in an accessible way, this 'how-to-guide' will help managers to make the most of these technologies in their business area"--

ISBN: 1137379286 (electronic bk.)

Source: 711154Palgrave Macmillanhttp://www.palgraveconnect.comSubjects--Topical Terms:

609582
Big data.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: HF5415.32 / .F56 2014

Dewey Class. No.: 658.8/3402856312

Predictive analytics, data mining and big data :myths, misconceptions and methods /
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245 1 0 $a Predictive analytics, data mining and big data : $b myths, misconceptions and methods / $c by Steven Finlay.
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505 0 $a 1. Introduction -- 2. Using Predictive Models -- 3. Analytics, Organization and Culture -- 4. The Value of Data -- 5. Ethics and Legislation -- 6. Types of Predictive Models -- 7. The Predictive Analytics Process -- 8. How to Build a Predictive Model -- 9. Text Mining and Social Network Analysis -- 10. Hardware, Software and All That Jazz.
520 $a "Predictive analytics, big data, and data mining are key topics for organizations who want to leverage the ever increasing amounts of data that organizations hold about their customers and other individuals. This in-depth guide provides readers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, the pitfalls and dangers, and a contextual road map for developing solutions that deliver benefits to their organizations. Written in an accessible way, this 'how-to-guide' will help managers to make the most of these technologies in their business area"-- $c Provided by publisher.
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650 7 $a BUSINESS & ECONOMICS / Development / General. $2 bisacsh $3 583372
650 7 $a BUSINESS & ECONOMICS / Knowledge Capital. $2 bisacsh $3 564298
650 7 $a BUSINESS & ECONOMICS / Marketing / Research. $2 bisacsh $3 645502
650 7 $a BUSINESS & ECONOMICS / Strategic Planning. $2 bisacsh $3 564272
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856 4 0 $3 Palgrave Connect $u https://link.springer.com/book/10.1057/9781137379283