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Big Data and Big Data Technologies

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Big Data in Healthcare

Abstract

The term Big Data often refers to the massive amount of digital information that companies and government organizations collect about entities (people and things), interactions of entities with each other and operations of systems in physical or virtual living environments.

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References

  1. Marz, N., Warren, J.: Big Data: Principles and Best Practices of Scalable Realtime Data Systems. Manning Publications Co. (2015)

    Google Scholar 

  2. Lohr, S.: The origins of “Big Data”: An etymological detective story. The New York Times

    Google Scholar 

  3. Amirian, P.,  Loggerenberg, F., Lang, T., Thomas, A., Peeling, R., Basiri, A., Goodman, S.: Using big data analytics to extract disease surveillance information from point of care diagnostic machines, Pervasive and Mobile Computing, 2017, ISSN 1574-1192, http://dx.doi.org/10.1016/j.pmcj.2017.06.013. (2017)

  4. Sumbaly, R., Kreps, J., Shah, S.: The big data ecosystem at LinkedIn. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 1125–1134. ACM, New York, NY, USA (2013)

    Google Scholar 

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

    Article  Google Scholar 

  6. Madsen, L.: Data-Driven Healthcare: How Analytics and BI are Transforming the Industry. Wiley (2014)

    Google Scholar 

  7. Provost, F., Fawcett, T.: Data Science for Business. O’Reilly Media (2013)

    Google Scholar 

  8. Amirian, P., Basiri, A., Van Loggerenberg, F., Moore, T., Lang, T., Varga, M.: Intersection of geospatial big data, geocomputation and cloud computing. In: 1st ICA European Symposium on Cartography, pp. 72–74 (2015)

    Google Scholar 

  9. Laney, D.: 3D data management: controlling data volume, velocity, and variety. (2001)

    Google Scholar 

  10. Hassanien, A.-E., Azar, A.T., Snasel, V., Kacprzyk, J., Abawajy, J.H.: Big Data in Complex Systems: Challenges and Opportunities. Springer (2015)

    Google Scholar 

  11. Amirian, P., Van Loggerenberg, F., Lang, T., Varga, M.: Geospatial Big Data for Finding Useful Insights from Machine Data. In: GISResearch UK 2015 (2015)

    Google Scholar 

  12. Ellis, B.: Real-time Analytics: Techniques to Analyze and Visualize Streaming Data. (2014)

    Google Scholar 

  13. Hitzler, P., Janowicz, K.: Linked Data, Big Data, and the 4th Paradigm. Semant. Web 4, 233–235 (2013)

    Google Scholar 

  14. Wamba, S.F., Akter, S., Edwards, A., Chopin, G., Gnanzou, D.: 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 

  15. Caldarola, E.G., Picariello, A., Castelluccia, D.: Modern enterprises in the bubble: why big data matters. ACM SIGSOFT Softw. Eng. Notes 40, 1–4 (2015)

    Article  Google Scholar 

  16. Laney, D.: Batman on Big Data, http://blogs.gartner.com/doug-laney/batman-on-big-data/

  17. Amirian, P., Basiri, A., Winstanley, A.: Efficient online sharing of geospatial big data using NoSQL XML databases. In: 2013 4th International Conference on Computing for Geospatial Research and Application (COM.Geo), pp. 152–159 (2013)

    Google Scholar 

  18. Ghemawat, S., Gobioff, H., Leung, S.T.: The Google file system. In: ACM SIGOPS Operating Systems Review, vol. 37, no. 5, pp. 29–43. ACM (2003, October)

    Google Scholar 

  19. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)

    Google Scholar 

  20. White, T.: Hadoop: The Definitive Guide. O’Reilly Media, Inc. (2012)

    Google Scholar 

  21. Erl, T., Khattak, W., Buhler, P.: Big Data Fundamentals: Concepts, Drivers & Techniques. Prentice Hall Press (2016)

    Google Scholar 

  22. Ramakrishnan, R., Sridharan, B., Douceur, J.R., Kasturi, P., Krishnamachari-Sampath, B., Krishnamoorthy, K., Sharman, N.: Azure Data Lake Store: A Hyperscale Distributed File Service for Big Data Analytics. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp. 51–63. ACM (2017, May)

    Google Scholar 

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Correspondence to Pouria Amirian .

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Amirian, P., van Loggerenberg, F., Lang, T. (2017). Big Data and Big Data Technologies. In: Amirian, P., Lang, T., van Loggerenberg, F. (eds) Big Data in Healthcare. SpringerBriefs in Pharmaceutical Science & Drug Development. Springer, Cham. https://doi.org/10.1007/978-3-319-62990-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-62990-2_3

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