Predictive analytics: Difference between revisions

Revision as of 09:18, 20 July 2025

Latest revision as of 13:27, 15 August 2025

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Predictive analytics is a set of business intelligence (BI) technologies that uncovers relationships and patterns within large volumes of data that can be used to predict behavior and events. Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future.<ref name=":4">{{Cite web |last=Eckerson |first=Wayne, W |date=2007 |title=Predictive Analytics. Extending the Value of Your Data Warehousing Investment |url=http://download.101com.com/pub/tdwi/files/pa_report_q107_f.pdf}}</ref> Predictive analytics statistical techniques include [[data modeling]], [[machine learning]], [[Artificial intelligence|AI]], [[deep learning]] algorithms and [[data mining]]. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future. For example, identifying suspects after a crime has been committed, or credit card fraud as it occurs.<ref>{{Cite book |last=Finlay |first=Steven |title=Predictive Analytics, Data Mining and Big Data. Myths, Misconceptions and Methods (1st ed.) |publisher=[[Palgrave Macmillan]] |year=2014 |isbn=978-1137379276 |___location=Basingstoke |pages=237 |language=English}}</ref> The core of predictive analytics relies on capturing relationships between [[explanatory variable]]s and the predicted variables from past occurrences, and exploiting them to predict the unknown outcome. It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions.<ref name=":52" />

Predictive analytics is often defined as predicting at a more detailed level of granularity, i.e., generating predictive scores (probabilities) for each individual organizational element. This distinguishes it from [[forecasting]]. For example, "Predictive analytics—Technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions."<ref>{{Cite book |last=Siegel |first=Eric |title=Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (1st ed.) |publisher=[[Wiley (publisher)|Wiley]] |year=2013 |isbn=978-1-1183-5685-2 |language=English}}</ref> In future industrial systems, the value of predictive analytics will be to predict and prevent potential issues to achieve near-zero break-down and further be integrated into [[prescriptive analytics]] for decision optimization.<ref>{{Cite book |last=Spalek |first=Seweryn |title=Data Analytics in Project Management |publisher=Taylor & Francis Group, LLC |year=2019 |language=English}}</ref>

== Analytical techniques ==

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* {{cite book |last1=Guidère |first1=Mathieu |last2=Howard |first2=N |last3=Argamon |first3=Sh. |author3-link=Shlomo Argamon |title=Rich Language Analysis for Counterterrorism |___location=Berlin, London, New York |publisher=Springer-Verlag |year=2009 |isbn=978-3-642-01140-5}}

* {{cite book |last=Mitchell |first=Tom |title=Machine Learning |___location=New York |publisher=[[McGraw-Hill]] |year=1997 |isbn=0-07-042807-7}}

* {{cite book |last=Siegel |first=Eric |title=Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die |publisher=[[John Wiley & Sons]] |year=2016 |isbn=978-1119145677}}

* {{cite book |last=Tukey |first=John |title=Exploratory Data Analysis |___location=New York |publisher=Addison-Wesley |year=1977 |isbn=0-201-07616-0 |url-access=registration |url=https://archive.org/details/exploratorydataa00tuke_0}}

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