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Big Data for the Greater Good pp 35–50Cite as

Big Data: A Global Overview

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Part of the book series: Studies in Big Data ((SBD,volume 42))

Abstract

More and more, society is learning how to live in a digital world that is becoming engulfed in data. Companies and organizations need to manage and deal with their data growth in a way that compliments the data getting bigger, faster and exponentially more voluminous. They must also learn to deal with data in new and different unstructured forms. This phenomenon is called Big Data. This chapter aims to present other definitions for Big Data, as well as technologies, analysis techniques, issues, challenges and trends related to Big Data. It also looks at the role and profile of the Data Scientist, in reference to functionality, academic background and required skills. The result is a global overview of what Big Data is, and how this new form is leading the world towards a new way of social construction, consumption and processes.

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References

  1. A. Affelt, Acting on big data a data scientist role for info pros. Online Search 38(5), 10–14 (2014)

    Google Scholar 

  2. D. Agrawal, Analytics based decision making. J. Indian Bus. Search 6, 332–340 (2014)

    Article  Google Scholar 

  3. A. Alexandrov, R. Bergmann, S. Ewen et al., The Stratosphere platform for big data analytics. VLDB J. 23, 939–964 (2014)

    Article  Google Scholar 

  4. J. Archenaa, E.A. Mary Anita, A survey of big data analytics in healthcare and government. Procedia Comput. Sci. 50, 408–413 (2015)

    Article  Google Scholar 

  5. M.D. Assunção, R.N. Calheiros, S. Bianchia et al., Big Data computing and clouds: trends and future directions. Parallel Distrib. Comput. 80, 03–15 (2013)

    Google Scholar 

  6. P. Barnaghi, A. Sheth, C. Henson, From data to actionable knowledge: big data challenges in the web of things. IEEE Intell. Syst. 28, 06–11 (2013)

    Article  Google Scholar 

  7. R. Buyya, K. Ramamohanarao, C. Leckie et al., Big data analytics-enhanced cloud computing: challenges, architectural elements, and future direction. IEEE (2015). https://doi.org/10.1109/ICPADS.2015.18

    Article  Google Scholar 

  8. A. Cardenas, P.K. Manadhata, S.P. Rajan, Big data analytics for security. IEEE Secur. Priv. 11(6), 74–76 (2013)

    Article  Google Scholar 

  9. H. Chen, R.H.L. Chiang, V.C. Storey et al., Business intelligence and analytics: from big data to big impact. MIS Q 36(4), 1165–1188 (2012)

    Google Scholar 

  10. M. Chen, S. Mao, Y. Liu, Big data: a survey. Mobile Netw. Appl. 19, 171–209 (2014)

    Article  Google Scholar 

  11. J. Chen, Y. Chen, X. Du et al., Big Data challenge: a data management perspective. Environ. Front. Comput. Sci. 7(2), 157–164 (2013)

    Article  MathSciNet  Google Scholar 

  12. P. Chen, C.Y. Zhang, Data-intensive applications, challenges, techniques and technologies: a survey on Big Data. Inform. Sci. 275, 314–347 (2014)

    Article  Google Scholar 

  13. T. Davenport, D.J. Patil, Data scientist: the sexiest job of the 21st century. Harv. Bus. Rev. (2012). https://doi.org/10.1080/01639374.2016.1245231

    Article  Google Scholar 

  14. Dawar N (2016) Use Big Data to create value for customers, not just target them. Harv. Bus. Rev. https://hbr.org/2016/08/use-big-data-to-create-value-for-customers-not-just-target-them. Accessed 8 Sept 2017

  15. S. Giest, Big data for policymaking: fad or fasttrack? Policy Sci. 50(3), 367–382 (2017)

    Article  Google Scholar 

  16. A. Gandomi, M. Raider, Beyond the hype: big data concepts, methods, and analytics. IJIM 35(2), 137–144 (2015)

    Google Scholar 

  17. S. Earley, The digital transformation: staying competitive. IT Prof. 16, 58–60 (2014)

    Article  Google Scholar 

  18. S. Earley, Analytics, machine learning, and the internet of things. IT Prof. 17, 10–13 (2015)

    Article  Google Scholar 

  19. N. Elgendy, A. Elragal, Big data analytics in support of the decision making process. Procedia Comput. Sci. 100, 1071–1084 (2016)

    Article  Google Scholar 

  20. K. Evans, Where in the world is my information? Giving people access to their data. IEEE Secur. Priv. 12(5), 78–81 (2014)

    Article  Google Scholar 

  21. C. Everett, Big data—the future of cyber-security or its latest threat? Comput. Fraud Secur. 9, 14–17 (2015)

    Article  Google Scholar 

  22. A. Gandomi, M. Haider, Beyond the hype: big data concepts, methods, and analytics. Int. J. Inform. Manage. 35(2), 137–144 (2015)

    Article  Google Scholar 

  23. B. Gupta, M. Goul, B. Dinter, Business intelligence and big data in higher education: status of a multi-year model curriculum development effort for business school undergraduates, MS graduates, and MBAs. Commun. Assoc. Inf. Syst. 36, 450–476 (2015)

    Google Scholar 

  24. K. Gillon, S. Aral, C.Y. Lin et al., Business analytics: radical shift or incremental change? Commun. Assoc. Inf. Syst. 34(1), 287–296 (2014)

    Google Scholar 

  25. D. Hand, Statistics and computing: the genesis of data science. Stat. Comput. 25, 705–711 (2015)

    Article  MathSciNet  Google Scholar 

  26. P. Helland, If you have too much data, then ‘Good Enough’ is Good Enough. Commun. ACM 54(6), 40–47 (2011)

    Article  Google Scholar 

  27. C. Ishikiriyama, Big data: um panorama global através de análise da literatura e survey. Dissertation, Universidade Federal Fluminense (2016)

    Google Scholar 

  28. N. Kabir, E. Carayannis, Big data, tacit knowledge and organizational competitiveness. J. Intell. Stud. Bus. 3(3), 220–228 (2013)

    Google Scholar 

  29. A. Katal, M. Wazid, R.H. Goudar, Big data: issues, challenges, tools and good practices. Contemp. Comput. (2013). https://doi.org/10.1109/ic3.2013.6612229

  30. N. Khan, I. Yaqoob, I. Abaker et al., Big data: survey, technologies, opportunities, and challenges. Sci. World J. (2014). https://doi.org/10.1155/2014/712826

    Article  Google Scholar 

  31. G.H. Kim, S. Trimi, J.H. Chung, Big-data applications in the government sector. Commun. ACM 57, 78–85 (2014)

    Article  Google Scholar 

  32. H. Koscielniak, A. Puto, Big Data in decision making process of enterprises. Procedia Comput. Sci. 65, 1052–1058 (2015)

    Article  Google Scholar 

  33. T. Kraska, Finding the needle in the big data systems haystack. IEEE Internet Comput. 17(1), 84–86 (2013)

    Article  Google Scholar 

  34. N. Kshetri, Big data’s impact on privacy, security and consumer welfare. Telecommun. Policy 38(11), 1134–1145 (2014)

    Article  Google Scholar 

  35. D. Laney, 3-D data management: controlling data volume velocity and variety (2001), http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf. Accessed 20 Dec 2015

  36. D. Laney, Gartner predicts three big data trends for business intelligence (2015), http://www.forbes.com/sites/gartnergroup/2015/02/12/gartner-predicts-three-big-data-trends-for-business-intelligence/#5cc6fd8366a2. Accessed 20 Dec 2015

  37. P.S.H. Leeflang, P.C. Verhoef, P. Dahlström et al., Challenges and solutions for marketing in a digital era. Eur. Manage. J. 32(1), 01–12 (2014)

    Article  Google Scholar 

  38. J. Lin, Is big data a transient problem? IEEE Internet Comput. 16(5), 86–90 (2015)

    Article  Google Scholar 

  39. S. Liu, W. Cui, Y. Wu et al., A survey on information visualization: recent advances and challenges. Vis. Comput. 30(12), 1373–1393 (2014)

    Article  Google Scholar 

  40. M. Maciejewski, To do more, better, faster and more cheaply: using big data in public administration. Int. Rev. Adm. Sci. 83(1S), 120–135 (2017)

    Article  Google Scholar 

  41. T. Matzner, Why privacy is not enough privacy in the context of and big data. J. Inf. 12(2), 93–106 (2014)

    Google Scholar 

  42. V. Mayer-Schonberger, K. Cukier, Big Data: como extrair volume, variedade, velocidade e valor da avalanche de informação cotidiana. Elsevier (2013)

    Google Scholar 

  43. D.E. O’Leary, Artificial intelligence and big data. IEEE Intell. Syst. 28, 96–99 (2013)

    Article  Google Scholar 

  44. D.J. Power, Using ‘Big Data’ for analytics and decision support. J. Decis. Syst. 23(2), 222–228 (2014)

    Article  Google Scholar 

  45. A. Picciano, The evolution of big data and learning analytics in American higher education. J. Asynchronous Learn. Netw. 16(3), 09–21 (2012)

    Google Scholar 

  46. F. Provost, T. Fawcett, Data Science and Its Relationship to Big Data and Data-Driven Decision Making (Mary Ann Liebert, Inc., 2013). https://doi.org/10.1089/big.2013.1508

    Article  Google Scholar 

  47. J. Reyes, The skinny on big data in education: learning analytics simplified. Techtrends 59(2), 75–80 (2015)

    Article  Google Scholar 

  48. M. Scherman, H. Krcmar, H. Hemsen et al., Big Data: an interdisciplinary opportunity for information systems research. Bus. Inf. Syst. Eng. 6(5), 261–266 (2014)

    Article  Google Scholar 

  49. J.P. Shim, A.M. French, J. Jablonski, Big data and analytics: issues, solutions, and ROI. Commun. Assoc. Inf. Syst. 37, 797–810 (2015)

    Google Scholar 

  50. P. Tambe, Big data investment, skills, and firm value. Manage. Sci. 60(6), 1452–1469 (2014)

    Article  Google Scholar 

  51. J. Tien, Big Data: unleashing information. J. Syst. Sci. Syst. Eng. 22(2), 127–151 (2013)

    Article  Google Scholar 

  52. W.M. To, L. Lai, Data analytics in China: trends, issues, and challenges. IT Prof. 17(4), 49–55 (2015)

    Article  Google Scholar 

  53. S. Vlaene, Data scientists aren’t domain experts. IT Prof. 15(6), 12–17 (2013)

    Article  Google Scholar 

  54. Z. Xiang, J.H. Gerdes, Z. Schwartz et al., What can big data and text analytics tell us about hotel guest experience and satisfaction? Int. J. Hospitality Manage. 44, 120–130 (2015)

    Article  Google Scholar 

  55. Y. Xiao, L.Y.Y. Lu, J.S. Liu et al., Knowledge diffusion path analysis of data quality literature: a main path analysis. J. Informetr. 8(3), 594–605 (2014)

    Article  Google Scholar 

  56. S.F. Wamba, S. Akter, A. Edwards et al., How ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study. Int. J. Prod. Econ. 165, 234–246 (2015)

    Article  Google Scholar 

  57. M. Waller, S. Fawcett, Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logistics 34(2), 77–84 (2013)

    Article  Google Scholar 

  58. H. Watson, Tutorial: big data analytics: concepts, technologies, and applications. Commun. Assoc. Inf. Syst. 34(65), 1247–1268 (2014)

    Google Scholar 

  59. B. Wixom, T. Ariyachandra, D. Douglas et al., The current state of business intelligence in academia: the arrival of big data. Commun. Assoc. Inf. Syst. 34, 01–13 (2014)

    Google Scholar 

  60. X. Wu, X. Zhu, G.Q. Wu et al., Data mining with big data. IEEE Trans. Knowl. Data Eng. 26(1), 97–107 (2014)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Universidade Federal Fluminense, Niteroi, Brazil

    Celia Satiko Ishikiriyama & Carlos Francisco Simoes Gomes

Authors
  1. Celia Satiko Ishikiriyama
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  2. Carlos Francisco Simoes Gomes
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Corresponding author

Correspondence to Celia Satiko Ishikiriyama .

Editor information

Editors and Affiliations

  1. Operations and Information Management, Aston Business School, Aston University, Birmingham, United Kingdom

    Ali Emrouznejad

  2. Buckingham Business School, University of Buckingham, Buckingham, United Kingdom

    Vincent Charles

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Ishikiriyama, C.S., Gomes, C.F.S. (2019). Big Data: A Global Overview. In: Emrouznejad, A., Charles, V. (eds) Big Data for the Greater Good. Studies in Big Data, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-93061-9_3

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