Prescriptive Analytics: A Survey of Emerging Trends And Technologies

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This paper provides a survey of the state-of-
the-art and future directions of one of the most important
emerging technologies within Business Analytics
(BA), namely Prescriptive Analytics (PSA). BA focuses
on data-driven decision making and consists of
three phases: Descriptive, Predictive, and Prescriptive
Analytics. While Descriptive and Predictive Analytics
allow us to analyze past and predict future events, respectively,
these activities do not provide any direct
support for decision making. Here, PSA lls the gap
between data and decisions. We have observed an increasing
interest for in-DBMS PSA systems in both research
and industry. Thus, this paper aims to provide
a foundation for PSA as a separate eld of study. To
do this, we rst describe the dierent phases of BA.
We then survey classical analytics systems and identify
their main limitations for supporting PSA, based
on which we introduce the criteria and methodology
used in our analysis. We next survey, categorize, and
discuss the state-of-the-art within emerging, so-called
PSA+, systems, followed by a presentation of the main
challenges and opportunities for next generation PSA
systems. Finally, the main ndings are discussed and
directions for future research are outlined.
Original languageEnglish
JournalV L D B Journal
Number of pages24
ISSN1066-8888
DOIs
Publication statusE-pub ahead of print - 26 May 2019

Cite this

@article{a9d5bd1fa82b4e7c8246bc14879329bc,
title = "Prescriptive Analytics: A Survey of Emerging Trends And Technologies",
abstract = "This paper provides a survey of the state-of-the-art and future directions of one of the most importantemerging technologies within Business Analytics(BA), namely Prescriptive Analytics (PSA). BA focuseson data-driven decision making and consists ofthree phases: Descriptive, Predictive, and PrescriptiveAnalytics. While Descriptive and Predictive Analyticsallow us to analyze past and predict future events, respectively,these activities do not provide any directsupport for decision making. Here, PSA lls the gapbetween data and decisions. We have observed an increasinginterest for in-DBMS PSA systems in both researchand industry. Thus, this paper aims to providea foundation for PSA as a separate eld of study. Todo this, we rst describe the dierent phases of BA.We then survey classical analytics systems and identifytheir main limitations for supporting PSA, basedon which we introduce the criteria and methodologyused in our analysis. We next survey, categorize, anddiscuss the state-of-the-art within emerging, so-calledPSA+, systems, followed by a presentation of the mainchallenges and opportunities for next generation PSAsystems. Finally, the main ndings are discussed anddirections for future research are outlined.",
author = "Davide Frazzetto and Nielsen, {Thomas Dyhre} and Pedersen, {Torben Bach} and Laurynas Siksnys",
year = "2019",
month = "5",
day = "26",
doi = "10.1007/s00778-019-00539-y",
language = "English",
journal = "V L D B Journal",
issn = "1066-8888",
publisher = "Springer",

}

Prescriptive Analytics: A Survey of Emerging Trends And Technologies. / Frazzetto, Davide; Nielsen, Thomas Dyhre; Pedersen, Torben Bach; Siksnys, Laurynas.

In: V L D B Journal, 26.05.2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Prescriptive Analytics: A Survey of Emerging Trends And Technologies

AU - Frazzetto, Davide

AU - Nielsen, Thomas Dyhre

AU - Pedersen, Torben Bach

AU - Siksnys, Laurynas

PY - 2019/5/26

Y1 - 2019/5/26

N2 - This paper provides a survey of the state-of-the-art and future directions of one of the most importantemerging technologies within Business Analytics(BA), namely Prescriptive Analytics (PSA). BA focuseson data-driven decision making and consists ofthree phases: Descriptive, Predictive, and PrescriptiveAnalytics. While Descriptive and Predictive Analyticsallow us to analyze past and predict future events, respectively,these activities do not provide any directsupport for decision making. Here, PSA lls the gapbetween data and decisions. We have observed an increasinginterest for in-DBMS PSA systems in both researchand industry. Thus, this paper aims to providea foundation for PSA as a separate eld of study. Todo this, we rst describe the dierent phases of BA.We then survey classical analytics systems and identifytheir main limitations for supporting PSA, basedon which we introduce the criteria and methodologyused in our analysis. We next survey, categorize, anddiscuss the state-of-the-art within emerging, so-calledPSA+, systems, followed by a presentation of the mainchallenges and opportunities for next generation PSAsystems. Finally, the main ndings are discussed anddirections for future research are outlined.

AB - This paper provides a survey of the state-of-the-art and future directions of one of the most importantemerging technologies within Business Analytics(BA), namely Prescriptive Analytics (PSA). BA focuseson data-driven decision making and consists ofthree phases: Descriptive, Predictive, and PrescriptiveAnalytics. While Descriptive and Predictive Analyticsallow us to analyze past and predict future events, respectively,these activities do not provide any directsupport for decision making. Here, PSA lls the gapbetween data and decisions. We have observed an increasinginterest for in-DBMS PSA systems in both researchand industry. Thus, this paper aims to providea foundation for PSA as a separate eld of study. Todo this, we rst describe the dierent phases of BA.We then survey classical analytics systems and identifytheir main limitations for supporting PSA, basedon which we introduce the criteria and methodologyused in our analysis. We next survey, categorize, anddiscuss the state-of-the-art within emerging, so-calledPSA+, systems, followed by a presentation of the mainchallenges and opportunities for next generation PSAsystems. Finally, the main ndings are discussed anddirections for future research are outlined.

U2 - 10.1007/s00778-019-00539-y

DO - 10.1007/s00778-019-00539-y

M3 - Journal article

JO - V L D B Journal

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