Business Intelligence (BI) system evolution: a case in a healthcare institution

Ehsanur Rahman Safwan, Rob Meredith, Frada Burstein

Research output: Chapter in Book/Report/Conference proceedingConference Paper

Abstract

Business Intelligence (BI) systems are an important part of many organisations’ IT portfolios. While the evolutionary nature of other kinds of decision support technology has been noted, there is little research investigating the evolutionary nature of BI systems. This paper presents a case study of a BI system development in a large Australian healthcare institution and uses evolutionary theories from decision support systems (DSS) to understand the system evolution observed. The paper concludes that the theories describing evolution in DSS can also be effectively applied to BI as well. BI practitioners and developers should be aware of evolutionary triggers, as well as the different kinds of evolution that can affect BI system evolution.

LanguageEnglish
Title of host publicationBig Data, Better Decisions, Brighter Future
Subtitle of host publicationProceedings of the 2016 Open Conference of the IFIP WG 8.3
EditorsDavid Sammon, Frada Burstein, Ciara Heavin, Gloria Philips-Wren, Frederic Adam, Ana Respicio
Place of PublicationAbingdon UK
PublisherTaylor & Francis
Pages463-475
Number of pages13
DOIs
StatePublished - 10 Jun 2016
EventIFIP International Conference on Decision Support Systems 2016 - University College Cork, Cork, Ireland
Duration: 22 Jun 201624 Jun 2016
Conference number: 18th
https://dss2016conference.wordpress.com/

Publication series

NameJournal of Decision Systems
PublisherTaylor & Francis
No.S1
Volume25
ISSN (Print)1246-0125
ISSN (Electronic)2116-7052

Conference

ConferenceIFIP International Conference on Decision Support Systems 2016
Abbreviated titleIFIP DSS 2016
CountryIreland
CityCork
Period22/06/1624/06/16
Internet address

Keywords

  • Business intelligence
  • Case study
  • Data warehousing
  • Healthcare
  • System evolution

Cite this

Safwan, E. R., Meredith, R., & Burstein, F. (2016). Business Intelligence (BI) system evolution: a case in a healthcare institution. In D. Sammon, F. Burstein, C. Heavin, G. Philips-Wren, F. Adam, & A. Respicio (Eds.), Big Data, Better Decisions, Brighter Future: Proceedings of the 2016 Open Conference of the IFIP WG 8.3 (pp. 463-475). (Journal of Decision Systems; Vol. 25, No. S1). Abingdon UK: Taylor & Francis. DOI: 10.1080/12460125.2016.1187384
Safwan, Ehsanur Rahman ; Meredith, Rob ; Burstein, Frada. / Business Intelligence (BI) system evolution : a case in a healthcare institution. Big Data, Better Decisions, Brighter Future: Proceedings of the 2016 Open Conference of the IFIP WG 8.3. editor / David Sammon ; Frada Burstein ; Ciara Heavin ; Gloria Philips-Wren ; Frederic Adam ; Ana Respicio. Abingdon UK : Taylor & Francis, 2016. pp. 463-475 (Journal of Decision Systems; S1).
@inproceedings{32f060ac8c324cbf9b91df41f85c2fa8,
title = "Business Intelligence (BI) system evolution: a case in a healthcare institution",
abstract = "Business Intelligence (BI) systems are an important part of many organisations’ IT portfolios. While the evolutionary nature of other kinds of decision support technology has been noted, there is little research investigating the evolutionary nature of BI systems. This paper presents a case study of a BI system development in a large Australian healthcare institution and uses evolutionary theories from decision support systems (DSS) to understand the system evolution observed. The paper concludes that the theories describing evolution in DSS can also be effectively applied to BI as well. BI practitioners and developers should be aware of evolutionary triggers, as well as the different kinds of evolution that can affect BI system evolution.",
keywords = "Business intelligence, Case study, Data warehousing, Healthcare, System evolution",
author = "Safwan, {Ehsanur Rahman} and Rob Meredith and Frada Burstein",
year = "2016",
month = "6",
day = "10",
doi = "10.1080/12460125.2016.1187384",
language = "English",
series = "Journal of Decision Systems",
publisher = "Taylor & Francis",
number = "S1",
pages = "463--475",
editor = "David Sammon and Frada Burstein and Ciara Heavin and Gloria Philips-Wren and Frederic Adam and Ana Respicio",
booktitle = "Big Data, Better Decisions, Brighter Future",
address = "United Kingdom",

}

Safwan, ER, Meredith, R & Burstein, F 2016, Business Intelligence (BI) system evolution: a case in a healthcare institution. in D Sammon, F Burstein, C Heavin, G Philips-Wren, F Adam & A Respicio (eds), Big Data, Better Decisions, Brighter Future: Proceedings of the 2016 Open Conference of the IFIP WG 8.3. Journal of Decision Systems, no. S1, vol. 25, Taylor & Francis, Abingdon UK, pp. 463-475, IFIP International Conference on Decision Support Systems 2016, Cork, Ireland, 22/06/16. DOI: 10.1080/12460125.2016.1187384

Business Intelligence (BI) system evolution : a case in a healthcare institution. / Safwan, Ehsanur Rahman; Meredith, Rob; Burstein, Frada.

Big Data, Better Decisions, Brighter Future: Proceedings of the 2016 Open Conference of the IFIP WG 8.3. ed. / David Sammon; Frada Burstein; Ciara Heavin; Gloria Philips-Wren; Frederic Adam; Ana Respicio. Abingdon UK : Taylor & Francis, 2016. p. 463-475 (Journal of Decision Systems; Vol. 25, No. S1).

Research output: Chapter in Book/Report/Conference proceedingConference Paper

TY - GEN

T1 - Business Intelligence (BI) system evolution

T2 - a case in a healthcare institution

AU - Safwan,Ehsanur Rahman

AU - Meredith,Rob

AU - Burstein,Frada

PY - 2016/6/10

Y1 - 2016/6/10

N2 - Business Intelligence (BI) systems are an important part of many organisations’ IT portfolios. While the evolutionary nature of other kinds of decision support technology has been noted, there is little research investigating the evolutionary nature of BI systems. This paper presents a case study of a BI system development in a large Australian healthcare institution and uses evolutionary theories from decision support systems (DSS) to understand the system evolution observed. The paper concludes that the theories describing evolution in DSS can also be effectively applied to BI as well. BI practitioners and developers should be aware of evolutionary triggers, as well as the different kinds of evolution that can affect BI system evolution.

AB - Business Intelligence (BI) systems are an important part of many organisations’ IT portfolios. While the evolutionary nature of other kinds of decision support technology has been noted, there is little research investigating the evolutionary nature of BI systems. This paper presents a case study of a BI system development in a large Australian healthcare institution and uses evolutionary theories from decision support systems (DSS) to understand the system evolution observed. The paper concludes that the theories describing evolution in DSS can also be effectively applied to BI as well. BI practitioners and developers should be aware of evolutionary triggers, as well as the different kinds of evolution that can affect BI system evolution.

KW - Business intelligence

KW - Case study

KW - Data warehousing

KW - Healthcare

KW - System evolution

UR - http://www.scopus.com/inward/record.url?scp=84976464743&partnerID=8YFLogxK

U2 - 10.1080/12460125.2016.1187384

DO - 10.1080/12460125.2016.1187384

M3 - Conference Paper

T3 - Journal of Decision Systems

SP - 463

EP - 475

BT - Big Data, Better Decisions, Brighter Future

PB - Taylor & Francis

CY - Abingdon UK

ER -

Safwan ER, Meredith R, Burstein F. Business Intelligence (BI) system evolution: a case in a healthcare institution. In Sammon D, Burstein F, Heavin C, Philips-Wren G, Adam F, Respicio A, editors, Big Data, Better Decisions, Brighter Future: Proceedings of the 2016 Open Conference of the IFIP WG 8.3. Abingdon UK: Taylor & Francis. 2016. p. 463-475. (Journal of Decision Systems; S1). Available from, DOI: 10.1080/12460125.2016.1187384