Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Predictive Analytics

  • Ugur CetintemelEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_80669


Predictive analytics


Predictive analytics refers to the practice of using a class of analytical techniques that involve data-driven modeling, mining, and learning over historical data to make predictions about missing, incomplete, or future data values, events, or patterns.

Main Text

Predictive analytics combines historical data with predictive models to produce additional information not readily available within the data.

Predictive analytics is often cited as a major analytics category along with descriptive analytics, which focuses on the analysis of historical data for postmortem insight, and prescriptive analytics that uses predicted data to help with antemortem decision making.

Predictive models that underlie predictive analytics are diverse yet they all commonly describe the relationships present in the data. The most popular models are based on regression (e.g., linear and logistic) and machine learning techniques (e.g., support vector machines and k-nearest...

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Recommended Readings

  1. 1.
    Mert Akdere, Ugur Çetintemel, Matteo Riondato, Eli Upfal, Stanley B. Zdonik. The case for predictive database systems: opportunities and challenges. In: Proceedings of the 5th Biennial Conference on Innovative Data Systems Research; 2011. p. 167–74.Google Scholar
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    Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D. Pednault, Berthold Reinwald, Vikas Sindhwani, Shirish Tatikonda, Yuanyuan Tian, Shivakumar Vaithyanathan. SystemML: declarative machine learning on MapReduce. In: Proceedings of the 27th International Conference on Data Engineering; 2011. p. 231–42.Google Scholar
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    Hellerstein JM, Ré C, Schoppmann F, Wang DZ, Fratkin E, Gorajek A, Ng KS, Welton C, Feng X, Li K, Kumar A. The MADlib analytics library or MAD skills, the SQL. Proc VLDB Endow. 2012;5(12):1700–11.CrossRefGoogle Scholar
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    Tim Kraska, Ameet Talwalkar, John C. Duchi, Rean Griffith, Michael J. Franklin, Michael I. Jordan. MLbase: a distributed machine-learning system. In: Proceedings of the 6th Biennial Conference on Innovative Data Systems Research; 2013.Google Scholar
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    Xixuan Feng, Arun Kumar, Benjamin Recht, Christopher Ré. Towards a unified architecture for in-RDBMS analytics. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2012. p. 325–36.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceBrown UniversityProvidenceUSA

Section editors and affiliations

  • Torben Bach Pedersen
    • 1
  • Stefano Rizzi
    • 2
  1. 1.Department of Computer ScienceAalborg UniversityAalborgDenmark
  2. 2.DISIUniv. of BolognaBolognaItaly