Business analytics : a management approach / Richard Vidgen, Sam Kirshner and Felix B. Tan.

By:

Vidgen, Richard

Contributor(s):

Material type: Text

TextPublisher: London : Red Globe Press, 2019Description: xiv, 430p. : ill. ; 26cmISBN:

9781352007251

Subject(s):

DDC classification:

658.4013 VID 22

Summary: This exciting new textbook offers an accessible, business-focused overview of the key theoretical concepts underpinning modern data analytics. It provides engaging and practical advice on using the key software tools, including SAS Visual Analytics, R and DataRobot, that are used in organisations to help make effective data-driven decisions. Combining theory with hands-on practical examples, this essential text includes cutting edge coverage of new areas of interest including social media analytics, design thinking and the ethical implications of using big data.

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Holdings
Item type	Current library	Collection	Call number	Status	Barcode
Books	CUoM Library General Stacks	Business Management/Accounting/Marketing	658.4013 VID (Browse shelf(Opens below))	Available	00012205

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Previous	658.4013 QUA Quality management /	658.4013 QUA Quality management /	658.4013 QUA Quality management /	658.4013 VID Business analytics : a management approach /	658.402 JOH Organization behaviour : understanding and managing life at work /	658.403 BAR Quantitative techniques for business decisions /	658.403 CYE A behavioral theory of the firm /	Next

Includes bibliographical references and index.

This exciting new textbook offers an accessible, business-focused overview of the key theoretical concepts underpinning modern data analytics. It provides engaging and practical advice on using the key software tools, including SAS Visual Analytics, R and DataRobot, that are used in organisations to help make effective data-driven decisions. Combining theory with hands-on practical examples, this essential text includes cutting edge coverage of new areas of interest including social media analytics, design thinking and the ethical implications of using big data.

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