Adopting Business Analytics to Leverage Enterprise Data Assets

dc.contributor.authorDjerdjouri, Mohamed
dc.contributor.authorMehailia, Abdelghani
dc.date.accessioned2022-04-26T07:48:06Z
dc.date.available2022-04-26T07:48:06Z
dc.date.copyright© 2017
dc.date.issued2017
dc.descriptionThis conference paper is not available at CUD collection. The version of scholarly record of this paper is published in Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy. Springer Proceedings in Business and Economics (2017), available online at: https://doi.org/10.1007/978-3-319-43434-6_5en_US
dc.description.abstractIn today’s rapidly changing business environment, advances in information and communication technologies are happening at a very fast pace. As a result, firms are under constant pressure to quickly adapt, be competitive, and identify new business opportunities. Also, the amount of data collected by organizations today is growing at an exponential rate and includes structured as well as new types of large and real-time data across a broad range of industries such as streaming, geospatial, social media, or sensor-generated data. Enterprise data have become an invaluable strategic asset. Many organizations are using modern Business Analytics (BA) to extract new insights and the maximum possible value from these data assets, which will enable them to make timely and accurate decisions. In this paper, we briefly describe business analytics and discuss how leading world class organizations are adopting it and the technology environments that make it relatively easy and inexpensive and, the subsequent competitive benefits they have achieved. In addition, we will report some findings from surveys of executives, managers, and professionals across industries about the use of analytics in their organizations, done recently by IBM, SAS, MIT, and Gartner. Also, we will briefly address the organizational, cultural, and technological challenges faced by organizations embracing business analytics. Finally, we will discuss the unique obstacles and challenges encountered by firms in developing countries with the goal of raising awareness of organizations in the MENA region not only about these impediments but also about the benefits of these technologies and the crucial role they play in the survival and competitiveness of the firm in the complex and turbulent global market. © 2017, Springer International Publishing Switzerland.en_US
dc.identifier.citationDjerdjouri, M. & Mehailia, A. (2017). Adopting Business Analytics to Leverage Enterprise Data Assets. In R. Benlamri & M. Sparer (Eds.) Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy. Springer Proceedings in Business and Economics, (pp. 57 - 67). Springer, Cham. https://doi.org/10.1007/978-3-319-43434-6_5en_US
dc.identifier.isbn978-331943433-9
dc.identifier.issn21987246
dc.identifier.urihttps://doi.org/10.1007/978-3-319-43434-6_5
dc.identifier.urihttp://hdl.handle.net/20.500.12519/559
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media B.V.en_US
dc.relationAuthors Affiliations : Djerdjouri, M., School of Business and Economics, State University of New York at Plattsburgh, Plattsburgh, NY, United States; Mehailia, A., School of Business Administration, Canadian University of Dubai, Dubai, United Arab Emirates
dc.relation.ispartofseriesLeadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy. Springer Proceedings in Business and Economics;
dc.rightsLicense to reuse the abstract has been secured from Springer Nature and Copyright Clearance Center.
dc.rights.holderCopyright : © 2017, Springer International Publishing Switzerland.
dc.rights.licenseLicense Number: 5277470499430 License date: Mar 28, 2022
dc.rights.urihttps://s100.copyright.com/CustomerAdmin/PLF.jsp?ref=61bc41bf-8582-410e-a101-11b2132d7184
dc.subjectBig dataen_US
dc.subjectBusiness analyticsen_US
dc.subjectCompetitive advantageen_US
dc.subjectDatasetsen_US
dc.titleAdopting Business Analytics to Leverage Enterprise Data Assetsen_US
dc.typeConference Paperen_US
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