Abstract
Big data is used to describe data so large, so complex a mix of structured and unstructured data, and so fast changing that it cannot be managed by conventional means; big data is often described in terms of the 3 V’s—volume, variety, and velocity. Due to big data’s size, our demand for real-time information, and the many different ways in which data might be stored, including within documents human ability to effectively manage data is further being challenged.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
See https://www.google.org/flutrends/about/. Google no longer publishes these trends but makes historical data available.
- 2.
Van der Muelen, R. “Managing the Data Chaos of Self-Service Analytics,” Gartner Research, December 17, 2015. http://www.gartner.com/smarterwithgartner/managing-the-data-chaos-of-self-service-analytics/.
- 3.
Federal Trade Commission, “Data Brokers—A Call for Transparency and Accountability,” May 2014. Examples of data brokers include Acxiom, Corelogic, Datalogix, eBureau, ID Analytics, Intelius, PeekYou, Rapleaf, and Recorded Future.
- 4.
See, for example, Ross, J. W., Beath, C. M., & Quadgraas, A., “You may not need big data after all—Learn how lots of little data can inform everyday decision making,” Harvard Business Review, December 2013.
- 5.
Almquist, E., Senior, J., & Springer, T., “Three promises and perils of big data,” Bain & Company, 2015. http://www.bain.com/Images/BAIN_BRIEF_Three_promises_and_perils_of_Big_Data.pdf.
- 6.
Heudecker, N., Beyer, M., & Edjlali, R., “The Demise of Big Data, Its Lessons and the State of Things to Come.” Gartner Research, August 19, 2015.
- 7.
See “The Federal Big Data Research and Development Strategic Plan,”https://www.nitrd.gov/PUBS/bigdatardstrategicplan.pdf.
- 8.
See “Seizing the information advantage How organizations can unlock value and insight from the information they hold,” PwC, September 2015. http://www.ironmountain.com/Knowledge-Center/Reference-Library/View-by-Document-Type/White-Papers-Briefs/S/~/media/Files/Iron%20Mountain/Knowledge%20Center/Reference%20Library/White%20Paper/S/Seizing%20The%20Information%20Advantage.pdf.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Fleckenstein, M., Fellows, L. (2018). Big Data and Data Management. In: Modern Data Strategy. Springer, Cham. https://doi.org/10.1007/978-3-319-68993-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-68993-7_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68992-0
Online ISBN: 978-3-319-68993-7
eBook Packages: Computer ScienceComputer Science (R0)