Uso Corporativo do Big Data: Uma Revisão de Literatura

Marcio Silveira; Carla Bonato Marcolin; Henrique Mello Rodrigues Freitas

doi:10.5585/gep.v6i3.369

Authors

Marcio Silveira UNIVERSIDADE NOVE DE JULHO
Carla Bonato Marcolin UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL
Henrique Mello Rodrigues Freitas UNIVERSIDADE NOVE DE JULHO

DOI:

https://doi.org/10.5585/gep.v6i3.369

Keywords:

Big Data, Business, Information Technology.

Abstract

The Big Data is a technological advent of processing large volumes of data that has gained notoriety because of opportunities and challenges around their usefulness in supporting the business. Therefore, this article, through a systematic literature review to identify how they are connected to Big Data and the corporate world. For this, 439 papers are investigated in terms of type of publication, annual trends in production, leading authors and institutions. As a result it was identified that there is a growing interest in the topic Big Data connected to business, both in the productions linked to scientific institutions, as those linked to companies. Were also observed theme leads to a very wide range of businesses, health marketing, or public transportation to education, always linked to better decision making.

References

Agrawal, D. (2014). Analytics based decision making. Journal of Indian Business Research, 6(4), 332–340.

Bartels, K., Barbeito, A. & Mackensen, G. B. (2011). The anesthesia team of the future. Current Opinion in Anesthesiology, 24(6), 687–692.

Berinato, S. (2014). With big data comes big responsibility. Harvard Business Review, Novembro.

Bishop, N. (2014). Spotlighting big data and analytics heroes. IBM Data Management Magazine, (1).

Björk, B. C., Welling, P., Laakso, M., Majlender, P., Hedlund, T. & Guonason, G. (2010). Open access to the scientific journal literature: situation 2009. PloS one, 5(6), e11273.

Blocker, A. W. & Meng, X.-L. (2013). The potential and perils of preprocessing: Building new foundations. Bernoulli, 19(4), 1176–1211.

Brereton, P., Kitchenham, B., Budgen, D., Turner, M. & Khalil, M. (2007). Lessons from applying the systematic literature review process within the software engineering domain. Journal of systems and software, 80(4), 571–583.

Chang, R. M., Kauffman, R. J. & Kwon, Y. (2014). Understanding the paradigm shift to computational social science in the presence of big data. Decision Support Systems, 63, 67–80.

Chen, H., Chiang, R. H. & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165–1188.

Chen, C. P. & Zhang, C.Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314–347.

Chen, M., Mao, S. & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171–209.

Chow-White, P. A. & Green, S. (2013). Data Mining Difference in the Age of Big Data: Communication and the social shaping of genome technologies from 1998 to 2007. International Journal of Communication, 7, 28.

Silva, I. M. & Campos, F. C. (2015). New perspectives using big data: a study of bibliometric 2000-2012. Anais da 11a Conferência Internacional sobre Sistemas de Informação e Gestão de Tecnologia, São Paulo, SP.

Davenport, T. H. (2014). How strategists use “big data” to support internal business decisions, discovery and production. Strategy and Leadership, 42(4), 45–50.

Davenport, T. H., Barth, P. & Bean, R. (2012). How “big data” is different. MIT Sloan Management Review, 54(1).

Demchenko, Y., Grosso, P., De Laat, C. & Membrey, P. (2013). Addressing Big Data issues in scientific data infrastructure. Colaboration Technologies ans Systems (CTS).

Demirkan, H. & Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), 412–421.

Freitas, H., Becker, J. L., Kladis, C. M. & Hoppen, N. (1997). Informação e decisão: Sistemas de apoio e seu impacto. Porto Alegre: Ortiz, 74.

Garcia Martinez, M. & Walton, B. (2014). The wisdom of crowds: The potential of online communities as a tool for data analysis. Technovation, 34(4), 203–214.

Goldman, A., Kon, F., Pereira Junior, F., Polato, I. & Pereira, R. (2012). Apache Hadoop: Conceitos teóricos e práticos, evoluçao e novas possibilidades. XXXI Jornadas de atualizaçoes em informatica.

Hayashi, A. M. (2014). Thriving in a Big Data World. MIT Sloan Management Review, 55(2), 35–39.

Huang, T. & Van Mieghem, J. A. (2014). Clickstream data and inventory management: Model and empirical analysis. Production and Operations Management, 23(3), 333–347.

Huwe, T. K. (2012). Big Data, Big Future. Computers in libraries, v. 32 (5), p. 20-22.

Jackson, S. (2014). Prediction, explanation and big(ger) data: a middle way to measuring and modelling the perceived success of a volunteer tourism sustainability campaign based on “nudging”. Current Issues in Tourism, p. 1-16.

James, R. (2014). Out of the box: Big data needs the information profession - the importance of validation. Business Information Review, 31(2), 118–121.

Kemp, R. (2014). Legal aspects of managing Big Data. Computer Law and Security Review, 30(5), 482–491.

Klingström, T., Soldatova, L., Stevens, R., Roos, T. et. al. (2013). Workshop on laboratory protocol standards for the molecular methods database. New biotechnology, 30(2), 109–113.

Leeflang, P. S. H., Verhoef, P., Dahlstrom, P. & Freundt, T. (2014). Challenges and solutions for marketing in a digital era. European Management Journal, 32(1), 1–12.

Llorente, R. & Morant, M. (2014). Wearable computers and big data: Interaction paradigms for knowledge building in higher education. In Innovation and Teaching Technologies: New Directions in Research, Practice and Policy (p. 127–137).

Luvizan, S.; Meirelles, F.; Diniz, E. H. (2014) Big Data: publication evolution and research opportunities. Anais da 11a Conferência Internacional sobre Sistemas de Informação e Gestão de Tecnologia. São Paulo, SP.

Manyika, J., et al. (2011). Big data: The next frontier for innovation, competition, and productivity. Recuperado de http://www.citeulike.org/group/18242/article/9341321. Acesso em Setembro 2015.

Marchand, D. A., Peppard, J. (2013). Why IT fumbles analytics. Harvard Business Review, 91(1), 104–112.

Mavandadi, S., Dimitrov, S., Feng, S., Yu, F., Yu, R.; et al. (2012). Crowd-sourced BioGames: managing the big data problem for next-generation lab-on-a-chip platforms. Lab on a chip, 12(20), 4102–4106.

Mayer-Schonberger, V. & Cukier, K. (2013). Big data: como extrair volume, variedade, velocidade e valor da avalanche de informação cotidiana (Vol. 1). Elsevier Brasi.

Mcafee, A. & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 4.

Millie, D. F., Weckman, G., Young, W., Ivey, J. et al.. (2013). Coastal “Big Data”and nature-inspired computation: Prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric. Estuarine, Coastal and Shelf Science, 125, 57–67.

Montejo-Ráez, A., Galiano, M., Martinnez-Santiago, F. & Urena-Lopez, L. (2014). Crowd explicit sentiment analysis. Knowledge-Based Systems, 69(1), 134–139.

Nash, D. B. (2014). Harnessing the power of big data in healthcare. American Health and Drug Benefits, 7(2), 69–70.

Park, H. W. & Leydesdorff, L. (2013). Decomposing social and semantic networks in emerging “big data” research. Journal of Informetrics, 7(3), 756–765.

Petroni, F., Querzoni, L., Beraldi, R. & Paolucci, M. (2014). LCBM: Statistics-based parallel collaborative filtering. Business Information Systems, v. 176, pp. 172-184.

Pousttchi, K. & Hufenbach, Y. (2014). Engineering the value network of the customer interface and marketing in the data-rich retail environment. International Journal of Electronic Commerce, 18(4), 17–41.

Rust, R. T. & Huang, M.-H. (2014). The service revolution and the transformation of marketing science. Marketing Science, 33(2), 206–221.

Sengupta, P. P. (2013). Intelligent platforms for disease assessment: novel approaches in functional echocardiography. JACC: Cardiovascular Imaging, 6(11), 1206–1211.

Shaw, R. (2014). The marketing data space race. Journal of Direct, Data and Digital Marketing Practice, 15(4), 260–261.

Shum, S. B., Aberer, K., Schmidt, A., Bishop, S. et al. (2012). Towards a global participatory platform. The European Physical Journal Special Topics, 214(1), 109–152.

Simpao, A. F., Ahumada, L., Galvez, J. & Rehman, M. (2014). A review of analytics and clinical informatics in health care. Journal of medical systems, 38(4), 1–7.

Tao, S., Corcoran, J., Mateo-Babiano, I. & Rohde, D. (2014). Exploring Bus Rapid Transit passenger travel behaviour using big data. Applied Geography, 53, 90–104.

Tien, J. M. (2013). Big data: Unleashing information. Journal of Systems Science and Systems Engineering, 22(2), 127–15.

Tranfield, D., Denyer, D. & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British journal of management, 14(3), 207–222.

Webster, J. & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. Management Information Systems Quarterly, 26(2), 3.

Wigan, M. R. & Clarke, R. (2013). Big data’s big unintended consequences. Computer, 46(6), 46–53.

Zikopoulos, P., Lightstone, S., Huras, M., Sachedina, A. et al. (2013). New dynamic in-memory analytics for the era of big data. IBM Data Management Magazine, (4), 1–47.