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Business Analytics: A Management Approach

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Business Analytics: A Management Approach

Business Analytics: A Management Approach
by Richard Vidgen (Author), Sam Kirshner (Author, Contributor), Felix Tan (Author, Contributor)

About the Author
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.

About this book
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.

Brief contents
Part I Business Analytics in Context
1. Introduction
2. Business Analytics Development
3. Data and Information
Part II Tools and Techniques
4. Data Exploration
5. Clustering and Segmentation
6. Predictive Modelling with Regression
7. Predictive Modelling with Logistic Regression
8. Predictive Modelling with Classification and Regression Trees
9. Visualization and Communication
10. Automated Machine Learning
11. R
12. Working with Unstructured Data
13. Social Networks
Part III Organizational Aspects
14. BUSINESS ANALYTICS DEVELOPMENT METHODOLOGY
15. Design and Agile Thinking
16. Ethical Aspects of Business Analytics

Length: 444 pages
Publisher: Red Globe Press; 1st ed. 2019 edition (September 28, 2019)
Language: English
ASIN: B07YHJ2T3T

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