Business Analytics - A Management Approach (Paperback, 1st Ed. 2019)

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. A wealth of learning features including exercises, cases, online resources and data sets help students to develop analytic problem-solving skills. With its management perspective on analytics and its coverage of a range of popular software tools, this is an ideal essential text for upper-level undergraduate, postgraduate and MBA students. It is also ideal for practitioners wanting to understand the broader organisational context of big data analysis and to engage critically with the tools and techniques of business analytics. Accompanying online resources for this title can be found at bloomsburyonlineresources.com/business-analytics. These resources are designed to support teaching and learning when using this textbook and are available at no extra cost.

General

Imprint:	Bloomsbury Academic
Country of origin:	United Kingdom
Release date:	October 2019
First published:	2019
Authors:	Richard Vidgen • Sam Kirshner • Felix Tan
Dimensions:	260 x 193 x 28mm (L x W x T)
Format:	Paperback
Pages:	446
Edition:	1st Ed. 2019
ISBN-13:	978-1-352-00725-1
Categories:	Books > Reference & Interdisciplinary > Communication studies > Data analysis Books > Business & Economics > Business & management > Sales & marketing > Market research Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	1-352-00725-8
Barcode:	9781352007251

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