Automation vs. Human Intervention: Is There any Room Left for the Analyst in the Data Mining Process?

Automation vs. Human Intervention: Is There any Room Left for the Analyst in the Data Mining Process?

Meryem Sevinc (Georgia Southern University, USA), Lawrence Locker (Georgia Southern University, USA) and John D. Murray (Georgia Southern University, USA)
Copyright: © 2009 |Pages: 11
DOI: 10.4018/978-1-60566-176-6.ch025
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In the contemporary context of knowledge discovery, the amount of information and the process itself has increased in complexity. Relevant to the present chapter is the increased reliance on automaticity in knowledge discovery. Although, there are positive benefits of automation, there is reason to believe that a process that emphasizes greater human participation may produce more meaningful results. Through a description of the human information processing system and its attributes, this chapter discusses why an analyst-centered approach to a knowledge discovery system is a desirable goal. We argue that a perspective based on cognitive psychology can serve as a useful guide in achieving a desirable synergy between automated knowledge discovery tools and the human analyst.
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In the present technological age, there is an increasing need in complex organizations for the rapid acquisition, interpretation, and practical application of data. Fifty years ago, it was considered a great success for organizations to be able to answer a question such as what their revenue had been over the previous four years. Today however, the questions are much more sophisticated, such as “What are the estimated unit sales over the next ten months?” and “What are the reasons behind these projections?” Technological advances such as efficient computer systems and the World Wide Web (WWW), now allow organization analysts to access easily enormous data sets which can, in turn, be analyzed in any number of ways that can be helpful to an organization. For example, a retail company could use available data to gain a better understanding of customer preferences, leading to more effective use of advertising dollars and overall improvement of marketing strategies. Alternatively, companies could use data for information about internal functioning that could lead to a better understanding of employee communication or effective use of technology. Indeed, in an age of competitive global markets, effective acquisition and use of data is not only a benefit, but may actually be necessary for an organization to stay competitive. Such a climate has led to the label “inquiring organizations” which refers to organizations that are involved in the creation of knowledge (e.g., data) that serves their mission to stay current and competitive (e.g., Churchman, 1971; Murray, Case, & Gardiner, 2005). Technological processes that are critical to inquiring organizations are Knowledge Discovery in Databases (KDD) and Data Mining (DM).

KDD refers to the general process of discovering useful information and patterns in datasets. DM is a specific form of KDD involving the use of computational algorithms to extract from large data sets information and statistical patterns that directly point to actionable findings. In this chapter we focus on the role of the data mining analyst, the individual who applies the computational algorithms to a data set and then interprets the output in light of the organizational goals for strategic change or improvement. Currently, there is a trend in DM towards a greater reliance on automation. That is, once the analyst selects the appropriate algorithms, their execution is largely automated (e.g., Murray et al., 2005). Consequently, the search for meaningful patterns is computer-based, whereas the role of the analyst is centered primarily on interpretation of outcomes. The heavy reliance on automation and relatively low analyst involvement in DM has benefits and liabilities. The benefits of a heavy reliance on automation include speed and efficiency with which data analytic processes can be executed. In contrast, a liability of an automated algorithm-execution stage is that the analyst is unable to flexibly employ and interject into the process valuable background experiences and domain knowledge. For example, in the “data extraction process” low analyst involvement may be associated with missed data or patterns. Stated differently, if pattern detection is left solely to a computer-based algorithm, then it is probable that many patterns will be discarded. Furthermore, some of these (discarded) patterns might, to a human analyst, be judged to be important based on the background knowledge of the analyst (e.g., an insight that might indicate a new approach to the data and consequently new model parameters that might lead to the identification of statistical patterns that might otherwise never be considered). We would argue that although automaticity has an invaluable pragmatic value in its ability to reduce large bodies of data to manageable proportions, it is also important to determine how the typically automated components of DM can be augmented by potentially valuable human (i.e., analyst) involvement given the rich knowledge and inferential abilities that humans bring to any task1. In this chapter, we will attempt to articulate why a heavily automated approach to KDD and DM is not an ideal goal and that such an approach diminishes the contributions from the (human) analyst.

To make our case, let us first turn to a discussion of KDD and the current state of DM. We will then turn to a description of the human information processing system in order to illustrate its strengths and flexibility. Finally we will discuss the importance of integrating the analyst into the DM process and how this might be accomplished.

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Editorial Advisory Board
Table of Contents
Dariusz Jemielniak, Jerzy Kociatkiewicz
Dariusz Jemielniak, Jerzy Kociatkiewicz
Chapter 1
Davydd J. Greenwood
This chapter questions the clarity of the concepts of “knowledge society” and “knowledge-intensive organization”. In particular, the author asserts... Sample PDF
Are Research Universities Knowledge-Intensive Learning Organizations?
Chapter 2
Juha Kettunen
The aims of knowledge management are to create knowledge and stimulate innovation. Knowledge management allows the knowledge of an organization to... Sample PDF
Construction of Knowledge-Intensive organizations in Higher Education
Chapter 3
Jeff Gold, Richard Thorpe
Continuing Professional Development (CPD) is usually conceived as a planned and formulated process for individual members of professional... Sample PDF
Collective CPD: Professional Learning in a Law Firm
Chapter 4
Paul Trott, Andreas Hoecht
The United States and European economies have witnessed an enormous increase in the amount of specialized business services, which now provide... Sample PDF
Innovation Risks of Outsourcing within Knowledge Intensive Business Services (KIBS)
Chapter 5
Lars Steiner
A new knowledge management perspective and tool, ANT/AUTOPOIESIS, for analysis of knowledge management in knowledge-intensive organizations is... Sample PDF
Actor-Network Theory and Autopoiesis: A New Perspective on Knowledge Management
Chapter 6
Jo A. Tyler, David M. Boje
This chapter fits the theme, the interplay between creativity and control in organizations. Story is often claimed to be a way to elicit tacit... Sample PDF
Sorting the Relationship of Tacit Knowledge to Story and Narrative Knowing
Chapter 7
Louise Grisoni
The central discussion in this chapter is that poetry can be used to provide a bridge between tangible, rational and explicit knowledge and tacit or... Sample PDF
Exploring Organizational Learning and Knowledge Exchange through Poetry
Chapter 8
Ester Barinaga
“How do we define our project goal?” “How are we going to coordinate our independent national studies?” “Who is responsible for what?” “How are... Sample PDF
Vagueness: The Role of Language in the Organizing Process of Knowledge Intensive Work
Chapter 9
Stephen Sheard
In this chapter the author offers an argument towards the resurgence of a proto-alphabetic imagination in electronic and mobile communications. It... Sample PDF
Tyranny of the Eye? The Resurgence of the Proto-Alphabetic Sensibility in Contemporary Electronic Modes of Media (PC/Mobile Telephony); and its Significance for the Status of Knowledge
Chapter 10
Krzysztof Klincewicz
The chapter discusses the role of IT Research & Analysis firms in the diffusion of knowledge management. The research is based on content analysis... Sample PDF
Knowledge Management and IT Research and Analysis Firms: Agenda-Setters, Oracles and Judges
Chapter 11
Fatima Guadamillas-Gomez, Mario J. Donate-Manzanares
This chapter analyses the implementation of knowledge management strategies (KMS) in technologyintensive firms. Firstly, a review of KMS in the... Sample PDF
Knowledge Management Strategies Implementation in Innovation Intensive Firms
Chapter 12
Arla Juntunen
This chapter focuses on the development of the Knowledge Management (KM) platform, and, more generally, the knowledge- and resource based view (RBV)... Sample PDF
Developing a Corporate Knowledge Management Platform in a Multibusiness Company
Chapter 13
Jonathan D. Owens
Success in new product development (NPD) can be considered a general aim for any company wishing to survive in the 21st Century. It has been found... Sample PDF
Modeling the New Product Development Process: The Value of a Product Development Process Model Approach as a Means for Business Survival in the 21st Century
Chapter 14
Anders Örtenblad
The ambition of this chapter is to pay some attention to more obvious, as well as more subtle, methods for organizations to become independent of... Sample PDF
Achieving Organizational Independence of Employees' Knowledge Using Knowledge Management, Organizational Learning, and the Learning Organization
Chapter 15
Angelo Ditillo
Knowledge-intensive firms are composed of various communities, each characterized by specialized knowledge. These communities operate as critical... Sample PDF
Balancing Stability and Innovation in Knowledge-Intensive Firms: The Role of Management Control Mechanisms
Chapter 16
Aino Kianto, Jianzhong Hong
Nowadays knowledge and competencies are the key productive factors, and the organizational capability for continuous learning, development and... Sample PDF
The Knowledge-Based Approach to Organizational Measurement: Exploring the Future of Organizational Assessment
Chapter 17
Vidar Hepsø
In knowledge management literature, common information spaces (CIS) are believed to be instrumental in the development and sharing of knowledge.... Sample PDF
Common Information Spaces in Knowledge-Intensive Work: Representation and Negotiation of Meaning in Computer-Supported Collaboration Rooms
Chapter 18
Agnieszka Postula
This chapter presents and discusses two factors – creativity and control – which correspond to every organizational reality. IT specialists’... Sample PDF
Creativitiy and Control in IT Professionals' Communities
Chapter 19
Patrocinio Zaragoza-Saez, Enrique Claver-Cortes, Diego Quer-Ramon
Knowledge is one of the basic production factors owned by enterprises, and knowledge management is one of the main dynamic capabilities on which... Sample PDF
A Qualitative Study of Knowledge Management: The Multinational Firm Point of View
Chapter 20
Cliff Bowan, Pauline Gleadle
The chapter addresses a central dilemma from the viewpoint of dynamic capabilities and the resource based view of the firm: how to manage creativity... Sample PDF
Culture as a Dynamic Capability: The Case of 3M in the United Kingdom
Chapter 21
Maria E. Burke
The purpose of this chapter is to consider an original way of improving Knowledge Management relationships. This is done within the context of an... Sample PDF
Cultural Issues, Organizations and Information Fulfillment: An Exploration Towards Improved Knowledge Management Relationships
Chapter 22
Darius Mehri
The author worked in the research and design department at a large Toyota company in the late 1990s and experienced an innovative process where... Sample PDF
Engineering Design at a Toyota Company: Knowledge Management and the Innovative Process
Chapter 23
Federica Ricceri, James Guthrie
The shift towards a knowledge based economy is at the core of the debate of contemporary management and accounting literature and organisations are... Sample PDF
Critical Analysis of International Guidelines for the Management of Knowledge Resources
Chapter 24
Christiane Prange
Internationalization has accelerated the speed of knowledge generation and innovation. Thus, companies increasingly need to pool and create new... Sample PDF
Strategic Alliance Capability: Bridging the Individual Back into Inter-Organizational Collaboration
Chapter 25
Meryem Sevinc, Lawrence Locker, John D. Murray
In the contemporary context of knowledge discovery, the amount of information and the process itself has increased in complexity. Relevant to the... Sample PDF
Automation vs. Human Intervention: Is There any Room Left for the Analyst in the Data Mining Process?
Chapter 26
Joanna Shih
The hi-tech firms that predominate in Silicon Valley contain a large proportion of knowledge workers—employees with high levels of education and... Sample PDF
Temporality and Knowledge Work
Chapter 27
Alice MacGilivray
Knowledge management is often associated with the need for change and related shifts in ontologies, ways of knowing and ways of working. Combine the... Sample PDF
Knowledge Intensive Work in a Network of Counter-Terrorism Communities
Chapter 28
Tatiana Andreeva
Contemporary literature usually views knowledge creation and knowledge sharing as either independent or positively related processes. However, based... Sample PDF
Tensions between Knowledge Creation and Knowledge Sharing: Individual Preferences of Employees in Knowledge-Intensive Organizations
Chapter 29
Steffen Boehm, Chris Land
Knowledge is implicitly assumed to form an increasingly important, or even the dominant source of values for today’s knowledge based organizations.... Sample PDF
The 'Value' of Knowledge: Reappraising Labour in the Post-Industrial Economy
Chapter 30
Alexander Styhre
This chapter discusses the use of media in knowledge-intensive organizations. Media is defined here as the integration of technologies, practices... Sample PDF
New Media and Knowledge Work
Chapter 31
Ben Tran
This chapter examines knowledge and innovation as invaluable factors affecting the longevity of large organizations. It presents the history and... Sample PDF
Knowledge Management: The Construction of Knowledge in Organizations
Chapter 32
Premilla D’Cruz, Ernesto Noronha
Scholars researching the area of the sociology of professions had earlier predicted that as occupations seek to improve their public image... Sample PDF
Redefining Professional: The Case of India's Call Center Agents
Chapter 33
Dariusz Jemielniak, Jerzy Kociatkiewicz
Knowledge management and knowledge-intensive work are two of today’s hot buzzwords, though both already have a history of managerial usage. While... Sample PDF
Knowledge Management: Fad or Enduring Organizational Concept?
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