Business Analytics
A Management Approach
Published on 9. October 2019
Book
Paperback/Softback
XIV, 430 pages
978-1-352-00725-1 (ISBN)
Description
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.Reviews / Votes
Yes, this is a book on business analytics - but it's really much broader. It encompasses up-to-the-minute topics like analysis of social media data, automated machine learning, visual analytics, open source tools, agile methods, and ethical issues like algorithmic bias. It's a complete and accurate guide to how analytics are currently practised in leading organizations. * Thomas H. Davenport, Babson College, USA * Provides an impressive overview of business analytics approaches to support a data-driven organisation, and runs the full gamut from understanding and analyzing big data, to designing the right business model for strategising and organising a leadership that drives analytics value creation. * Leroy White, Warwick Business School, UK * In an age where information matters for business survival, companies need to understand and appreciate the value derived from data. Business Analytics provides a toolkit for the practitioner to unlock said value. I would highly recommend it to executives and students who are thinking about or already on the analytics journey. * Yudhvir Seetharam, University of the Witwatersrand, South Africa * This is a great book for introducing MBA students into the area of business analytics with up-to-date information, a comprehensive coverage of topics and clear explanations for the non-specialist. It reflects a careful approach to use analytics for creating value in business. * Martin Kunc, Southampton Business School, UK *More details
Edition
1st ed. 2019
Language
English
Place of publication
London
United Kingdom
Publishing group
Bloomsbury Publishing PLC
Target group
College/higher education
Illustrations
349 farbige Abbildungen, 20 farbige Tabellen
4 bw illus
Dimensions
Height: 276 mm
Width: 203 mm
Thickness: 24 mm
Weight
1032 gr
ISBN-13
978-1-352-00725-1 (9781352007251)
DOI
10.26777/978-1-352-00726-8
Schweitzer Classification
Other editions
Additional editions
E-Book
09/2019
1st Edition
Bloomsbury Academic
€71.99
Available for download
Persons
RICHARD VIDGEN is Professor of Business Analytics at the University of New South Wales Business School, Australia and Emeritus Professor of Systems Thinking at the University of Hull, UK.
SAM KIRSHNER is a Senior Lecturer in Operations Management and Business Analytics at the University of New South Wales Business School, Australia.
FELIX TAN is a Senior Lecturer in Information Systems at the University of New South Wales Business School, Australia.
SAM KIRSHNER is a Senior Lecturer in Operations Management and Business Analytics at the University of New South Wales Business School, Australia.
FELIX TAN is a Senior Lecturer in Information Systems at the University of New South Wales Business School, Australia.
Content
Introduction.- Business Analytics Development.- Data and Information.- Data Exploration.- Clustering and Segmentation.- Multiple Linear Regression.- Classification and Regression Trees (CART).- Visualization and Communication.- Automated Machine Learning.- R.- Working with Unstructured Data.- Social Networks.- Business Analytics Methodology.- Design and Agile Thinking.- Ethical Aspects.- Appendix A: Dataset Descriptions.- Appendix B: GoGet Case Study.- Appendix C: Business Analytics Capability Assessment (BACA) Survey.