1,465
Views
38
CrossRef citations to date
0
Altmetric
Themed Articles: Business Intelligence

Augmenting Data Warehouses with Big Data

, , &

REFERENCES

  • Agarwal, R. & Dhar, V. (2014). Editorial—Big data, data science, and analytics: The opportunity and challenge for is research. Information Systems Research, 25(3), 443–448. doi:10.1287/isre.2014.0546
  • Biehn, N. (2013). The missing V’s in big data: Viability and value. Wired. Retrieved January 10, 2015, from http://www.wired.com
  • Biju, T. & Bryla, B. (2002). OCA/OCP: Oracle9i DBA fundamentals I study guide: Exam 1Z0-031. New York, NY: John Wiley & Son.
  • Davenport, T. H., Barth, P., & Bean, R. (2012). How big data is different. MIT Sloan Management Review, 54(1), 43–46.
  • Devlin, B. (2012). Will data warehousing survive the advent of big data? O’Reilly Radar. Retrieved January 10, 2015, from http://radar.oreilly.com
  • Franks, B. (2012). Taming the big data tidal wave. New York, NY: John Wiley & Son.
  • Franks, B. (2014). The analytics revolution. New York, NY: John Wiley & Son.
  • Goes, P. B. (2014). Big data and is research. MIS Quarterly, 38(3), iii–viii.
  • Grimes, S. (2013). Big data: Avoid ‘Wanna V’ confusion. Information Week. Retrieved January 10, 2015, http://www.informationweek.com
  • Hitzler, P. & Janowicz, K. (2013). Linked data, big data, and the 4th paradigm. Semantic Web, 4, 233–235.
  • Höller, J., Tsiatsis, V., Mulligan, C., Karnouskos, S., Avesand, S., & Boyle, D. (2014). From machine-to-machine to the internet of things: Introduction to a new age of intelligence. Amsterdam, The Netherlands: Elsevier.
  • Jukic, N., Vrbsky, S., & Nestorov, S. (2013). Database systems—Introduction to databases and data warehouses. Upper Saddle River, NJ: Pearson/Prentice Hall.
  • Kimball, R. (2012). New emerging best practices for big data—A Kimball group white paper. Kimball Group. Retrieved January 10, 2015, from http://www.kimballgroup.com
  • Knilans, E. (2014). The 5 V’s of big data. Avnet Technology Solutions. Retrieved January 10, 2015, from http://www.ats.avnet.com
  • Laney, D. (2001). 3-D data management: Controlling data volume, velocity, and variety. META Group Report, File 949, February 2001. Stamford, CT: META Group Inc.
  • Lopez, K. & D’Antoni, J. (2014). The modern data warehouse—How big data impacts analytics architecture. BI Journal, 19(3), 8–15.
  • McAfee, A. & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 61–68.
  • Normandeau, K. (2013). Beyond volume, variety, and velocity is the issue of big data veracity. Inside Big Data. Retrieved January 10, 2015, from http://insidebigdata.com
  • Sicular, S. (2013). Gartner’s big data definition consists of three parts, not to be confused with three “V”s. Forbes. Retrieved January 10, 2015, from http://www.forbes.com

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.