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On the Need of Opening the Big Data Landscape to Everyone: Challenges and New Trends

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Notes

  1. 1.

    Apache Pig. https://pig.apache.org.

  2. 2.

    Apache Spark. http://spark.apache.org.

  3. 3.

    Apache Hive. https://hive.apache.org.

  4. 4.

    Apache HBase. https://hbase.apache.org.

  5. 5.

    Cloudera Impala. https://cloudera.com/products/apache-hadoop/impala.html.

  6. 6.

    Microsoft Azure Machine Learning. https://azure.microsoft.com/en-us/services/machine-learning.

  7. 7.

    Amazon Web Services. https://aws.amazon.com.

  8. 8.

    IBM Watson. http://www.ibm.com/watson.

  9. 9.

    IBM Watson Health. http://www.ibm.com/watson/health.

  10. 10.

    IBM InfoSphere. https://www-01.ibm.com/software/data/infosphere.

  11. 11.

    IBM BigData. https://www-01.ibm.com/software/data/bigdata.

  12. 12.

    Xplenty. https://www.xplenty.com.

  13. 13.

    WorkGenesis. http://www.workgenesis.com.

References

  1. R. van der Meulen and V. Woods, “Gartner survey shows more than 75 percent of companies are investing or planning to invest in Big Data in the next two years,” Gartner, 2015. [Online]. Available: http://www.gartner.com/newsroom/id/3130817.

  2. D. Simchi-Levi, J. Gadewadikar, B. McCarthy and L. LaFiandra, “Winning with analytics,” Accenture, 2015.

    Google Scholar 

  3. M. Turck, “Is Big Data still a thing? (The 2016 Big Data landscape),” FirstMark Capital, 2016. [Online]. Available: http://mattturck.com/2016/02/01/big-data-landscape.

  4. D. Loshin, “Achieving organizational alignment for Big Data analytics,” in Big Data Analytics, Morgan Kaufmann, 2013, pp. 21–28.

    Chapter  Google Scholar 

  5. Workflow Management Coalition, “Terminology & Glossary,” 1999.

    Google Scholar 

  6. J. Yu and R. Buyya, “A taxonomy of workflow management systems for grid computing,” Journal of Grid Computing, vol. 3, no. 3, pp. 171–200, 2006.

    Google Scholar 

  7. R. Frye and M. McKenney, Information granularity, big data, and computational intelligence, Springer, 2015.

    Google Scholar 

  8. T. White, Hadoop: The definitive guide, O’Reilly Media, 2015.

    Google Scholar 

  9. IBM Software, “Data-driven healthcare organizations use big data analytics for big gains,” 2013.

    Google Scholar 

  10. B. Kayyali, D. Knott and S. Van Kuiken, “The ‘big data’ revolution in healthcare: Accelerating value and innovation,” McKinsey & Company, 2013.

    Google Scholar 

  11. D. Adamson, “Big Data in healthcare made simple: Where it stands today and where it’s going,” [Online]. Available: https://www.healthcatalyst.com/big-data-in-healthcare-made-simple. [Accessed 10 08 2016].

  12. W. Liu, Q. Li, Y. Cai, Y. Li and X. Li, “A prototype of healthcare big data processing system based on Spark,” in 8th International Conference on Biomedical Engineering and Informatics, 2015.

    Book  Google Scholar 

  13. S. Rallapalli, R. R. Gondkar and U. P. K. Ketavarapu, “Impact of processing and analyzing healthcare Big Data on cloud computing environment by implementing Hadoop cluster,” Procedia Computer Science, vol. 85, pp. 16–22, 2016.

    Article  Google Scholar 

  14. L. Skiftenes Flak, W. Dertz, A. Jansen, J. Krogstie, I. Spjelkavik and S. Ølnes, “What is the value of eGovernment – and how can we actually realize it?,” Transforming Government: People, Process and Policy, vol. 3, no. 3, pp. 220–226, 2009.

    Article  Google Scholar 

  15. E. Kalampokis, E. Tambouris and K. Tarabanis, “A classification scheme for open government data: Towards linking decentralised data,” International Journal of Web Engineering and Technology, vol. 6, no. 3, pp. 266–285, 2011.

    Article  Google Scholar 

  16. The White House, “Transparency and Open Government. Memorandum for the heads of executive departments and agencies,” 2009. [Online]. Available: https://www.whitehouse.gov/sites/default/files/omb/assets/memoranda_fy2009/m09-12.pdf.

  17. V. Vijayakumar, V. Neelanarayanan, J. Archenaa and E. A. Mary Anita, “Big Data, cloud and computing challenges A survey of Big Data analytics in healthcare and government,” Procedia Computer Science, vol. 50, pp. 408–413, 2015.

    Article  Google Scholar 

  18. G.-H. Kim, S. Trimi and J.-H. Chung, “Big-data applications in the government sector,” Communications of the ACM, vol. 57, no. 3, pp. 78–85, 2014.

    Article  Google Scholar 

  19. B. Esmaeilian, S. Behdad and B. Wang, “The evolution and future of manufacturing: A review,” Journal of Manufacturing Systems, vol. 39, pp. 79–100, 2016.

    Article  Google Scholar 

  20. Oracle Enterprise Architecture, “Improving manufacturing performance with Big Data. Architect’s guide and reference architecture introduction,” 2015.

    Google Scholar 

  21. M. Gaitho, “How applications of Big Data drive industries,” 2015. [Online]. Available: http://www.simplilearn.com/big-data-applications-in-industries-article.

  22. C.-S. Neumann, “Big data versus big congestion: Using information to improve transport,” McKinsey & Company, 2015.

    Google Scholar 

  23. B. Marr, “Big Data: The winning formula in sports,” Forbes, 2015.

    Google Scholar 

  24. Y. Zhang and Y. Zhao, “Astronomy in the Big Data Era,” Data Science Journal, vol. 14, 2015.

    Google Scholar 

  25. Deloitte, “Opportunities in telecom sector: Arising from Big Data,” 2015.

    Google Scholar 

  26. M. R. Berthold, N. Cebron, F. Dill, T. R. Gabriel, T. Kötter, T. Meinl, P. Ohl, C. Sieb, K. Thiel and B. Wiswedel, “KNIME: The Konstanz Information Miner,” in Studies in Classification, Data Analysis, and Knowledge Organization, Springer, 2007.

    Google Scholar 

  27. M. Hofmann and R. Klinkenberg, RapidMiner: Data mining use cases and business analytics applications, Chapman & Hall/CRC, 2013.

    Google Scholar 

  28. K. Wolstencroft, R. Haines, D. Fellows, A. Williams, D. Withers, S. Owen, S. Soiland-Reyes, I. Dunlop, A. Nenadic, P. Fisher, J. Bhagat, K. Belhajjame and F. Bacall, “The Taverna workflow suite: Designing and executing workflows of web services on the desktop, web or in the cloud,” Nucleic Acids Research, vol. 41, no. W1, pp. W557–W561, 2013.

    Article  Google Scholar 

  29. KNIME, “Outlier detection in medical claims,” [Online]. Available: https://www.knime.org/knime-applications/outlier-detection-in-medical-claims. [Accessed 15 08 2016].

Further Reading

  1. D. C. Schmidt, “Guest editor’s introduction: Model-driven engineering,” Computer, vol. 39, pp. 25–31, 2006.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Córdoba, Córdoba, Spain

    Rubén Salado-Cid, Aurora Ramírez & José Raúl Romero

Authors
  1. Rubén Salado-Cid
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  2. Aurora Ramírez
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  3. José Raúl Romero
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Corresponding author

Correspondence to Rubén Salado-Cid .

Editor information

Editors and Affiliations

  1. Institut für Informatik, LMU München, Munich, Bayern, Germany

    Claudia Linnhoff-Popien

  2. Allianz SE, Munich, Bayern, Germany

    Ralf Schneider

  3. Munich Airport, Munich, Bayern, Germany

    Michael Zaddach

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Salado-Cid, R., Ramírez, A., Romero, J.R. (2018). On the Need of Opening the Big Data Landscape to Everyone: Challenges and New Trends. In: Linnhoff-Popien, C., Schneider, R., Zaddach, M. (eds) Digital Marketplaces Unleashed. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49275-8_60

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  • DOI: https://doi.org/10.1007/978-3-662-49275-8_60

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