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Dan Power

Greetings to all of my friends who work in the area of computerized decision support. This blog is a way for me to share stories from my encounters related to decision support, to comment on industry events, and to comment on other blogger's comments, especially those of my friends on the Business Intelligence Network. I'll try to state my opinions clearly and provide an old professor's perspective on how computers and information technology are changing the world. Decision making has always been my focus, and it will be in this blog as well. Your comments, feedback and questions are welcomed.

About the author >

Daniel J. "Dan" Power is a Professor of Information Systems and Management at the College of Business Administration at the University of Northern Iowa and the editor of DSSResources.com, the Web-based knowledge repository about computerized systems that support decision making; the editor of PlanningSkills.com; and the editor of DSS News, a bi-weekly e-newsletter. Dr. Power's research interests include the design and development of decision support systems and how these systems impact individual and organizational decision behavior.

Editor's Note: More articles and resources are available in Dan's BeyeNETWORK Expert Channel. Be sure to visit today!

D. J. Power, C. Heavin, J. McDermott & M. Daly


Searches of the Web using Google, and database searches of the academic and practitioner literature, return a large number of differing and varied definitions of the concept of business analytics. This article reviews the growing literature on Business Analytics (BA) using traditional and qualitative research tools. Our searches included using Google Search to identify examples of business analytics applications, and a focused keyword search of the available practitioner and academic literatures. Text analytics techniques identified frequently used terms in prior definitions of business analytics. Our empirical, inductive approach provides a basis for proposing and explaining a formal sentence definition for Business Analytics. The analysis provides a starting point for operationalising a measure for the business analytics construct. Additionally, understanding business analytics can help managers assess skill deficiencies and evaluate claims about relevance of tools and techniques. Finally, carefully defining the Business Analytics concept should provide stimulus for new research ideas. 

To cite this article: D. J. Power, C. Heavin, J. McDermott & M. Daly (2018) Defining business analytics: an empirical approach, Journal of Business Analytics, 1:1, 40-53, DOI: 10.1080/2573234X.2018.1507605

Posted August 29, 2018 8:24 AM
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Free download:

Power, D. J. (2016), "'Big Brother' can watch us," Journal of Decision Systems,
Special Issue the Proceedings of the 2016 Open Conference of the IFIP WG 8.3, "Big Data, Better Decisions, Brighter Future", Edited By: David Sammon, Frada Burstein, Ciara Heavin, Gloria Philips-Wren, Frederic Adam and Ana Respicio, Volume 25, Supplement 1, 2016, pp. 578-588. Published online on June 16, 2016 at URL 

Privacy, surveillance, and government abuse of data are concerns of many people in our complex digital world. 'Big Brother' in the title of this article is a metaphorical warning about the consequences if government uses modern technologies to maintain power and control people. Issues related to the abuse of data and surveillance are not new in the academic literature and mass market media, the current threat is however greater. Technology has advanced to the point where George Orwell's dystopian 'Big Brother' vision of a totalitarian state is possible. Because of technology advances, barriers associated with collecting and processing real-time data about many millions of individuals have been removed. This article explores how the capture and use of new data streams, and processing with AI and predictive analytics can support government control of its citizens. Some components of a system for thought control and real-time surveillance are already in use. These components like cameras, sensors, No SQL databases, predictive analytics, and artificial intelligence can be connected and improved. Decision support researchers must understand the issues and resist attempts to use information technologies to support current or future totalitarian governments.

Posted June 28, 2016 9:07 AM
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Power, D.J., "Data science: supporting decision-making," Journal of Decision Systems, published online April 25, 2016 at URL http://www.tandfonline.com/doi/full/10.1080/12460125.2016.1171610.


Data science is a new academic trans-discipline that builds on 60 years of research about supporting decision-making in organisations. It is an important and potentially significant concept and practice. Contemplating the need for data scientists encourages academics and managers to examine issues of decision-maker rationality, data and data analysis needs, analytical tools, job skills and academic preparation. This article explores data science and the data professionals who will use new data streams and analytics to support decision-making. It also examines the dimensions that are changing in the data stream and the skills needed by data scientists to analyse the new data streams. Organisations need data scientists, but academics need to understand the new data science jobs to prepare more people to support decision-making.

Posted June 14, 2016 11:23 PM
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by Daniel J. Power
Editor, DSSResources.com 

Personal and organizational factors, cultural factors, decision factors, information factors and psychological factors vary among decision situations. Every decision situation can not and should not be supported with a computerized decision support system (DSS). A major alternative is to conduct a special study using some computer-based analyses. Given that some decision situations are better supported by preparing a one-time special study, what factors indicate that it is more appropriate to prepare a special study than build a decision support system?

Continue reading this classic column at http://dssresources.com/faq/index.php?action=artikel&id=26

Please cite as:

Power, D. J. "What factors indicate a special study is more appropriate than a DSS?" Decision Support News, Vol. 16, No. 25, December 27, 2015 at URL http://dssresources.com/newsletters/410.php

Posted December 27, 2015 11:41 AM
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by Daniel J. Power
Editor, DSSResources.com 

Data mining is a data analysis innovation first discussed in the 1990s. "Big data" and analytics has led to a renewed and expanded interest in data mining technologies. Academics tend to use the related terms Knowledge Discovery and Intelligent Decision Support Methods (Dhar and Stein, 1997) or more derogatory terms like data surfing or data dredging. In general, data mining is a group of analytical methods like neural networks, genetic algorithms, and decision trees, that help people conduct computerized searchs for patterns in a data set. Data mining is both a process and a set of tools.

Continue reading at http://dssresources.com/faq/index.php?action=artikel&id=39

Please cite as:

Power, D. J. "What is data mining and how is it related to DSS?" Decision Support News, Vol. 16, No. 23, November 29, 2015 at URL http://dssresources.com/newsletters/408.php

Posted November 29, 2015 10:12 AM
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