Data, information and analytics as services

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Abstract

While organizations are trying to become more agile to better respond to market changes in the midst of rapidly globalizing competition by adopting service orientation—commoditization of business processes, architectures, software, infrastructures and platforms—they are also facing new challenges. In this article, we provide a conceptual framework for service oriented managerial decision making process, and briefly explain the potential impact of service oriented architecture (SOA) and cloud computing on data, information and analytics. Today, SOA, cloud computing, Web 2.0 and Web 3.0 are converging, and transforming the information technology ecosystem for the better while imposing new complexities. With this convergence, a large amount of structured and unstructured data is being created and shared over disparate networks and virtual communities. To cope and/or to take advantage of these changes, we are in need of finding new and more efficient ways to collect, store, transform, share, utilize and dispose data, information and analytics.

Highlights

► SOA helping to commoditize business processes, architectures and infrastructures. ► Managerial decision making processes can greatly benefit from SOA offerings. ► SOA, cloud computing, Web 2.0/3.0 are all collectively transforming the IT ecosystem. ► Data, information and analytics are becoming primary beneficiaries of SOA. ► Business analytics can be categorized into descriptive, predictive and prescriptive analytics.

Introduction

Service oriented thinking is one of the fastest growing paradigms in today's business world [3]. Most of the organizations have already built or are in the process of building decision support systems that utilize agile data, information and analytics capabilities as services. The concept of data, information and analytics as services advocates the view that—with the emergence of service-oriented business processes, architecture and infrastructure which include standardized processes for accessing data and analytics “where they live”—the actual platform on which the data or analytic tools resides should not matter. Data can reside in a local computer or in a server at a server farm in a cloud computing environment [1]. With data-as-a-service, any business process can access data wherever it resides, and with analytics-as-a-service can make sense out of the data using analytic tools wherever they may be located. Data and information‐as-a-service began with the notion that data—wherever they may reside and whatever form they may be in—can be integrated, cleansed and enriched at a centralized location (often on a virtual network infrastructure) and made available to different systems, applications or users. Also, the concept of analytics-as-a-service—often referred to as Agile Analytics—is fueled by the idea of turning utility computing and virtualization into a service model for analytics [12].

This special issue is aimed at soliciting and publishing cutting-edge research to better understand the effects of service orientation on data, information and analytics. Specifically, we wanted to have a collection of articles that provide insight into (1) how data, information and analytic services are different from traditional data access, manipulation and distribution frameworks, (2) what the primary reasons, costs and benefits are in implementing a service oriented architecture for management of data, information and analytics, (3) what the bases are for evaluating relevant technical and managerial approaches to service-oriented data, information and analytics, and (4) what be the prevailing approaches would be for governance mechanisms of such systems. With the papers accepted for this special issue, we think we have shed some light to addressing these issues.

The rest of the paper is organized as follows. In Section 2, we propose a high-level conceptual framework for service-oriented decision support systems. In Section 3, we provide a description of business analytics and ramification of its service-orientation. In Section 4, we summarize the papers accepted for this special issue, and in Section 5 we conclude the paper.

Section snippets

Service oriented decision support systems

Service orientation is gaining popularity in decision support systems. Such an architectural structure enables systems developers to rapidly configure/re-configure complex systems using a number of loosely-coupled components representing data, model and user interface as individual services. This type of service-oriented decision support system not only provides a flexible development environment, but also ensures effective and efficient use of computational resources to produce more accurate,

Analytics‐as‐a‐service

Compared to data and information-as-a‐service, analytics-as-a‐service is a relatively newer concept in the business world. Complexity of model management, development of service-based analytic models and standardizing the interfaces between the models are among the unique challenges that made analytics-as-a‐service a late-emergent information technology endeavor.

Analytics facilitates realization of business objectives through reporting of data to analyze trends, creating predictive models to

Introduction of the papers

This section provides a short description of the papers included in the special issue. These papers serve as a good representation of the diversity of research topics in service-oriented decision support systems.

The paper by Dong and Sirinivasan is about agent-enabled service-oriented decision support systems. In their paper, as part of the motivation for their study, they argue that the recent emphasis on web enablement as the next step in design improvements for decision support system

Concluding remarks

Today, utilization of service orientation, cloud computing and Web 2.0 and 3.0 are growing exponentially. As part of this utilization process, organizations generate and share more data and information than ever before. Owing to the increasing computational capabilities coupled with decreasing acquisition and operational costs, organizations are building capabilities to collect and store more structured and unstructured data and to transform them to meaningful information about their customers,

Dr. Dursun Delen is the William S. Spears Chair in Business Administration and Associate Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University (OSU). He received his Ph.D. in Industrial Engineering and Management from OSU in 1997. Prior to his appointment as an Assistant Professor at OSU in 2001, he worked for a private consultancy company, Knowledge Based Systems Inc., in College Station, Texas, as a research scientist for five

References (14)

  • H. Demirkan et al.

    Service-oriented technology and management: perspectives on research and practice for the coming decade

    The Electronic Commerce Research and Applications Journal

    (Fall 2008)
  • D.J. Abadi

    Data management in the cloud: limitations and opportunities

    IEEE Data Engineering Bulletin

    (March 2009)
  • A. Agarwal

    Web 3.0 concepts explained in plain English, digital inspiration

  • H. Demirkan, M. Goul, Taking value-networks to the cloud services: security services, semantics and service level...
  • H. Demirkan et al.

    Service-oriented Web application framework: utility-grade instrumentation of emergent Web applications

    The Special Issue of the IEEE IT Professional on the Future of Web Applications: Strategies and Design

    (September/October 2011)
  • J. Hendler

    Web 3.0 emerging

    IEEE Computer

    (January 2009)
  • I. Lustig et al.

    The analytics journey

There are more references available in the full text version of this article.

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Dr. Dursun Delen is the William S. Spears Chair in Business Administration and Associate Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University (OSU). He received his Ph.D. in Industrial Engineering and Management from OSU in 1997. Prior to his appointment as an Assistant Professor at OSU in 2001, he worked for a private consultancy company, Knowledge Based Systems Inc., in College Station, Texas, as a research scientist for five years, during which he led a number of decision support and other information systems related research projects funded by federal agencies such as DoD, NASA, NIST and DOE. His research has appeared in major journals including Decision Support Systems, Communications of the ACM, Computers and Operations Research, Computers in Industry, Journal of Production Operations Management, Artificial Intelligence in Medicine, Expert Systems with Applications, among others. He recently published three books on business intelligence, decision support systems and advanced data mining techniques. He is often invited to national and international conferences for keynote addresses on topics related to business intelligence, decision support systems, knowledge management and data mining. He served as the general co-chair for the 4th International Conference on Network Computing and Advanced Information Management (September 2–4, 2008 in Soul, South Korea), and regularly chairs tracks and mini-tracks at various information systems conferences. He is the associate editor-in-chief for International Journal of Experimental Algorithms, associate editor for International Journal of RF Technologies, and is on editorial boards of five other technical journals. His research and teaching interests are in decision support systems, data and text mining, knowledge management, business intelligence and enterprise modeling.

Dr. Haluk Demirkan is a Professor of information systems, and a Research Faculty of the Center for Services Leadership. His research and teaching interests are on service science and sustainable innovations, business-, social- and cloud services-intelligence and analytics, service supply chain management and commoditized service-oriented information systems. He has authored or co-authored almost 100 publications. Some of his articles appeared in Decision Support Systems, Journal of Service Research, Journal of Management Information Systems, Journal of the Association for Information Systems, IEEE Transactions Systems, Man & Cybernetics, European Journal of Operational Research, the Electronic Commerce Research & Applications Journal, and Communications of the ACM. He has recently co-edited two research books titled “The Science of Service Systems” and “Implementation of Service Systems.” Most recently, in 2011, he was ranked 50th in Top-100 Rankings of World-wide Researchers according to the Association for Information Systems sanctioned Research Rankings. He also received the IBM Faculty Award. He has more than fifteen years of professional work experience on how to maximize the return on companies' resources by effectively implementing enterprise business intelligence solutions with companies such as American Express, Bank of America, IBM, Intel, Premier Healthcare, MicroStrategy, Darden Restaurants, Eckerd Corporation and Lending Tree among others. He is a board member for Teradata University Network; Service Research and Innovation Institute; INFORMS and AIS Service Science Sections, and Global Text Project. Dr. Demirkan holds a Ph.D. in the Department of Information Systems & Operations Management; Post Master of Engineering and Master of Engineering in Industrial & Systems Engineering from the University of Florida, and BS in Mechanical Engineering from Istanbul Technical University.

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