Relevant bibliographies by topics / Business intelligence systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Business intelligence systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 May 2022

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Journal articles on the topic "Business intelligence systems"

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Tunowski, Remigiusz. "Organization Effectiveness and Business Intelligence Systems. Literature Review." Management and Business Administration. Central Europe 23, no. 4 (December 15, 2015): 55–73. http://dx.doi.org/10.7206/mba.ce.2084-3356.157.

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Stecyk, Adam. "Business Intelligence systems in SMEs." European Journal of Service Management 27 (2018): 409–13. http://dx.doi.org/10.18276/ejsm.2018.27/2-50.

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Rouhani, Saeed, Amir Ashrafi, Ahad Zare Ravasan, and Samira Afshari. "Business Intelligence Systems Adoption Model." Journal of Organizational and End User Computing 30, no. 2 (April 2018): 43–70. http://dx.doi.org/10.4018/joeuc.2018040103.

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Decision support and business intelligence systems have been increasingly adopted in organizations, while understanding the nature of affecting factors on such adoption decisions need receiving much academic interest. This article attempts to provide an in-depth analysis toward understanding the critical factors which affect the decision to adopt business intelligence (BI) in the context of banking and financial industry. In this regard, it examines a conceptual model that shows the impacts of different technological, organizational, and environmental factors in the decision to adopt BI by a firm. Structural equation modeling (SEM) was used for data analysis and test the relevant hypothesis. The results of this article which are derived from theoretical discussion of hypothesizes show that from nine hypothesized relationships—perceived tangible and intangible benefits, firm size, organizational readiness, strategy, industry competition and competitors absorptive capacity—affect BIS adoption in the surveyed cases.
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Francesco Di Tria, Ezio Lefons, and Filippo Tangorra. "Evaluation of Business Intelligence Systems." International Journal of Information Processing and Management 4, no. 3 (May 31, 2013): 222–37. http://dx.doi.org/10.4156/ijipm.vol4.issue3.22.

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Grünwald, Markus, and Dirk Taubner. "Business Intelligence." Informatik-Spektrum 32, no. 5 (August 27, 2009): 398–403. http://dx.doi.org/10.1007/s00287-009-0374-1.

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Herring, Jan P. "Business Intelligence." Journal of Business Strategy 14, no. 3 (March 1993): 10–12. http://dx.doi.org/10.1108/eb039552.

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Hawking, Paul, and Carmine Sellitto. "Business Intelligence Strategy." International Journal of Enterprise Information Systems 11, no. 1 (January 2015): 1–12. http://dx.doi.org/10.4018/ijeis.2015010101.

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Although Business Intelligence is seen as priority by many companies, the level of benefits achieved varies significantly between firms. Researchers have indicated that not having an effective Business Intelligence strategy is a significant issue in regards to trying to realize organizational benefits. This paper adopting a case study method investigates an Australian energy company's Business Intelligence adoption and the development of a Business Intelligence strategy that directly informed the firm's information needs. The important elements of this strategy included using a set of guiding principles to ensure that there was a close alignment of Business Intelligence outcomes with the company's needs. The paper provides insights for researchers and practitioners on the important factors need to be considered to achieve effective Business Intelligence.
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Glancy, Fletcher H., and Surya B. Yadav. "Business Intelligence Conceptual Model." International Journal of Business Intelligence Research 2, no. 2 (April 2011): 48–66. http://dx.doi.org/10.4018/jbir.2011040104.

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A business intelligence conceptual model (BISCOM) is proposed as a process-focused design theory for developing, understanding, and evaluating business intelligence (BI) systems. Previous work has concentrated on subsets of the BI systems, use of BI tools, and specific business functional area requirements. BISCOM provides a unified and comprehensive design theory that integrates and synthesizes existing research. It extends existing research by proposing functionality that does not currently exist in BI systems. The BISCOM is validated through descriptive methods that demonstrate the model utility and through prototype creation to demonstrate the need for BISCOM.
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Stecyk, Adam. "A development of Business Intelligence Systems." European Journal of Service Management 28 (2018): 305–11. http://dx.doi.org/10.18276/ejsm.2018.28/1-38.

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Jason, Gary, Paul Harmon, and David King. "Expert Systems: Artificial Intelligence in Business." Technology and Culture 28, no. 4 (October 1987): 894. http://dx.doi.org/10.2307/3105218.

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Dissertations / Theses on the topic "Business intelligence systems"

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Crossland, Maria. "How business intelligence is adding business value." Master's thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/10287.

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Includes bibliographical references (leaves 67-72).
Business Intelligence (BI) continues to top the list of CIO priorities, investment in BI technologies continues to grow and organizations are becoming increasingly reliant on BI to help reduce costs and grow revenues. However, structured measurement and monitoring of the business value that can be attributed to BI investment remain elusive. This study used a multiple case study approach to examine how BI is adding value to organizations, what processes and methods are being followed for the evaluation of the business value that BI delivers as well as what approaches are being used to maximize the potential value that the organization's investment on BI could deliver.
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Kashora, Kudzai. "Leveraging mobile business intelligence to create strategic business value." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13218.

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Currently, there is a growing need for mobile Business Intelligence (BI) in the business world as the nature of work is changing and employees are more mobile than ever before. Mobile BI promises portability and pervasive access to BI, making it a topic high on many directors’ agendas; however the tangible and intangible benefits of mobile BI are still not well understood. Coupled with this, BI practitioners’ are sceptical about the real business value of delivering BI reports to mobile devices and how this undertaking can bring about organizational changes in the long run. As the field of mobile BI is still in its infancy, there is a lack of research which addresses the business value of mobile BI. The existing studies in this research area have been focused on adoption and implementation strategies. This study therefore attempts to address the gap by investigating how mobile BI can be utilised to enhance organizational performance and also contribute towards strategic business value. In light of this, an extensive literature review was conducted which revealed that mobile BI usage can result in benefits, such as improved employee performance management, organizational agility and customer satisfaction. A conceptual model was developed based on the literature and this model acted as the framework for investigating the research problem.
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Chamoun, Christoffer. "Self-Service Business Intelligence : Kritiska framgångsfaktorer för att tillämpa Self-Service Business Intelligence." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15645.

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Self-service Business Intelligence är idag ett relativt nytt koncept och det blir vanligare idag att verksamheter börjar röra sig mot denna nya trend inom Business Intelligence för att att göra sina användare mer flexibla i sitt beslutsfattande. Anpassningen idag till Self- service BI är idag är låg och har sjunkit de senare trots stora investeringar. Konceptet med Self-service BI är kan vara svårt för användarna att förstå och det finns ett antal faktorer som kan bidra till att öka anpassningen och uppnå framgångar med att tillämpa SSBI. Denna studien syftar till att ta reda på: ”Vad finns det för kritiska framgångsfaktorer för att tillämpa Self-Service BI? ”. För att besvara frågan användes en kvalitativ metod och insamlingen för data utfördes med hjälp av semistrukturerade intervjuer. Intervjuerna utfördes på 6 företag med 6 olika respondenter som har erfarenhet inom SSBI och BI. Respondenterna bidrog med empirisk underlag för att kunna besvara studiens frågeställning, men även till litteraturen med information som litteraturen tidigare inte nämner. Resultaten har visat att svaren från respondenterna och litteraturen går i linje med varandra när det gäller kritiska framgångsfaktorer. Framgångsfaktorerna som diskuteras och tas upp av respondenterna och litteraturen var: Rätt verktyg för rätt användare & anpassningsbara användargränssnitt, utbildning, data governance & data management, kartlägga användare och tillgänglighet av data för att framgångsrikt tillämpa SSBI. Nya faktorer som framkom under de semistrukturerade intervjuerna med respondenterna var: Change management, kommunikation och experimentering & testning.
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Ahmad, Tanvir. "Design and Implementation of Business Intelligence Systems." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-156662.

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The goal of this project was to investigate the limitations of current Business Intelligence System (BI System) which was needed to re-design its architecture and embed two new modules. These two modules were named as Survey Form and Statistics Report. The survey form has a very dynamic behavior, for example the administrator can generate different types of surveys instantly by drag drop quick functionality of the interface and he can also send that surveys to the users. The user will give the answers of survey questions and send them back to the management of the company where survey form modules helped them to analyze the answers in the form of graphs. This survey form is also providing five different types of scheduling system where administrator can schedule their surveys in five different ways like Once, weekly, Monthly, Quarterly and Yearly. Statistics module has different behaviors. It implemented four different types of reports which are inter-related with each other. These four reports were named as financial report, human resource report, project overview and company overview. The finance report was responsible that it will show the revenue amount and source, from where the company generated this revenue. The second report was belonged to human resource department which was responsible for generating the overall situation of the employees and their projects. For example how many are on holidays, idle, working and going to be free soon. The third report was representing the projects overview of all the projects. This report is responsible for checking the status of all projects and show them in bar char who will show the management that how many projects are completed, going to start or delay and going to finish soon. The fourth and final report was responsible for generating report for the overall company status. This project has been completed successfully. The design, architecture and, implementation of intelligent Survey Form and Statics modules have been implemented and working successfully.
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Khalaf, Patrik. "Mobile business intelligence : För en lyckad mobile business intelligence lösning." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15752.

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Allt fler organisationer börjar se nyttan med Business Intelligence och varför det bör implementeras i sin verksamhet. Genom att använda sig av beslutsstödsystem kan organisationer samla ihop och bearbeta affärs-data och på så sätt få ut mer av sin verksamhet. Idag räcker det inte längre att ha tillgång till endast företagsinformationen inom verksamheten utan det behövs också kunna utnyttja realtids datan genom de mobila enheterna, detta genom Mobile Business Intelligence. Det handlar om en mobil variant av den traditionella business Intelligence (BI).  Med tanke på den mobila användningen ökade tillgängligheten samt prestandan i mobila enheter, så finns det stora möjligheter för Mobile BI ute i verksamheterna. Mobile BI som vilket nytt system som helst kommer även en viss problematik, kritiska framgångsfaktorer har analyserats och utvärderats. Inom dimensionen organisationsstöd identifierades två framgångsfaktorer som kunde styrkas vid namn managementsupport och skickligheter & kunskaper. Utöver dessa kunde även ytterligare två framgångsfaktorer styrkas som kritiska, nämligen datasäkerhet och användbarheten genom den begränsade skärm-ytan. Med denna studie ska det underlätta och göra det enklare för verksamheter att implementera Mobile BI i sin verksamhet. Studien tar upp viktiga framgångsfaktorer vid en implementation av Mobile BI och vad organisationer bör ha i åtanke.
More and more organizations are beginning to see the benefits of Business Intelligence and why it should be implemented into their business. By using decision support systems, organizations can merge and process business data and thus get more out of their business. Today, access to business information within the business is no longer sufficient, but it also needs to be able to use real-time data through the mobile devices. This through Mobile Business Intelligence, which is about a mobile variant of the traditional business intelligence (BI). Given the current mobile usage and how it has increased accessibility and mobile device performance, there are great opportunities for Mobile BI in the business. Mobile BI as any new system will also come with a certain problematic and critical success factors have been analyzed and evaluated. Within the organizational support dimension, two success factors were identified that was confirmed critical by name management support and knowledge and skills. In addition to these, another two success factors could be proved critical, named data security and usability through the limited screen area. With this study, it will facilitate and make it easier for businesses to implement Mobile BI in their operations. The study addresses key success factors in implementing Mobile BI and what organizations should keep in mind.
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Lindahl, Alexander, and Joel Gustafsson. "Business Intelligence för små företag." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-386497.

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Globaliseringen av ekonomin har genererat globaliseringen av information som varje chef har att hantera snabbt och effektivt i beslutsprocessen. Små företag är mer sårbara för att ändra affärsvillkor än större konkurrenter. För att överleva i den instabila ekonomiska miljön där de är verksamma måste småföretag kunna monitorera sina affärer och använda alla sina resurser effektivt, särskilt informationsresurser. Under det senaste decenniet har användningen av business intelligence vuxit fram som ett måste för att inte tappa marknadsfördelar. Huvudsyftet med denna uppsats är att utvärdera hur business intelligence kan tas fram och implementeras i små företag. För att göra detta genomfördes ett design science research projekt där en IT- artefakt utvecklades med CRISP-DM som metod. Både IT-artefakten och metoden CRISP-DM utvärderas i uppsatsens analys. Arbetat mynnar ut i slutsatsen att CRISP-DM inte är lämpad som metod för denna typ av projekt. Slutligen kommer vi fram till de faktorer som härstammar från ett företags storlek som påverkar framtagningen av BI-system.
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Robles, Sebastian. "Business intelligence in Chile, recommendations to develop local applications." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/70831.

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Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, June 2011.
"February 2010." Cataloged from PDF version of thesis.
Includes bibliographical references (p. 60).
The volume of information generated from enterprise applications is growing exponentially, and the cost of storage is decreasing rapidly. In addition, cloud-based applications, mobile devices and social networks are becoming relevant sources of unstructured data that provide essential information for strategic decisions making. Therefore, with time, enterprise databases will become more valuable for business but also much harder to integrate, process and analyze. Business Intelligence software was instrumental in helping organizations to analyze information and provide reports to support business decision-making. Accordingly, BI applications evolved as enterprise information grew, hardware-processing capacities developed, and storage cost is being reduced significantly. In this paper, we will analyze the current BI world market and compare it with the Chilean market, in order to come up with business plan recommendations for local developers and systems integrators interested in capitalizing the opportunities generated by the global BI software market consolidation.
by Sebastian Robles.
S.M.in Engineering and Management
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El, Harbiti Deeb. "Web-based spreadsheets and Business Intelligence : Combining a web-based spreadsheet with Pentahos Business Intelligence." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-324998.

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Business Intelligence is becoming more and more an essential element for a company’s planning, development and consistency. A company usually aims to predict and optimize the outcome of different decisions. In order to do that, it requires a tool that can perform scenario analysis or “what if” – analysis. These analyses can be performed with spreadsheets and today with the tools within business analysis being web-based, the purpose of the project is to combine a web-based spreadsheet with an analysis from a BI server. The BI server provides sample data. Should a combination be possible then a continuing goal would be to connect the BI server with a database and in that way provide the spreadsheet with data to perform “what if” – analysis. The results indicated that a combination between the web-based spreadsheet and the BI server was possible. However, a few alterations of the spreadsheet are still necessary in order for the combination to work as desired. Further developments of the product involve managing to adapt it to smartphones and tablets.
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McHenry, John James. "Exploring Best Practices to Utilize Business Intelligence Systems." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2742.

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Organizational leaders who can manage business intelligence system (BIS) resources may achieve sustainable success in economic, political, and corporate environments. The review of professional literature indicated that effective resource management in a BIS environment requires the establishment of best practice. The purpose of this qualitative, single-case study was to explore best practices among 9 BIS practitioners for effective resource management. Participation criteria included the active engagement in BIS professional disciplines and the willingness to share their perspectives. The conceptual framework for this study was the cognitive experiential self-theory (CEST). Five leaders and 4 data analysts at an eastern U.S. county government agency were interviewed. Using computer based qualitative data analysis software to assist with the coding process, interview transcripts and the published directives of government agency leaders were reviewed to identify themes and achieve triangulation. Five themes emerged: the need for comprehensive policies and procedures for creating operating standards, updated data acquisition training, human capital dynamics management for improved efficiency, protocols for transforming raw information into knowledge, and safeguards for preventing bias in data analysis. Findings derived from this study could contribute to global social change as BIS leaders use best practices to improve resource and data management proficiencies for rapidly transforming information into knowledge for developing policies, services, and regulations that affect public safety, fiscal planning, and social risk management.
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Johansson, Christoffer. "Self service business intelligence : Grundkompetenser för slutanvändare." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15630.

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Organisationer vill hela tiden bli effektivare i allt de gör även när det kommer till business intelligence. För att effektivisera beslutstödsprocessen har organisationer börjat gå över till selfe service business intelligence där personer på en operativ nivå skapar sina egna rapporter och gör sina egna analyser. När detta sker uppkommer nya moment för personalen i organisationen och de behöver skaffa sig nya kompetenser. Vilka kunskaper behöver egentligen personalen skaffa sig? Det är det som undersöks i det här arbetet. Undersökningen kommer genomföras med hjälp av en fallstudie. Litteratur kommer att granskas och intervjuer kommer att genomföras med personer som arbetar med beslutstöd. Arbetet undersöker vilka kompetenser som krävs av en slutanvändare men exkluderar hur de skaffar sig dessa kompetenser. Resultatet visar att det finns tre stycken huvudkategorier av kompetenser dessa är tekniska kunskaper, verksamhetskunskaper och analytiska förmågor. Under dessa kategorier finns sedan sex stycken kompetenser; Verksamhetsdata, BI-verktyget, Datavana, Verksamheten, Branschkunskap och Analytisktänk.
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Books on the topic "Business intelligence systems"

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Decision support systems for business intelligence. 2nd ed. Hoboken, N.J: Wiley, 2010.

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1949-, King David, ed. Expert systems: Artificial intelligence in business. New York: J. Wiley, 1985.

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Turban, Efraim. Decision support and business intelligence systems. 9th ed. Upper Saddle River, N.J: Pearson/Prentice Hall, 2011.

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Sauter, Vicki L. Decision Support Systems for Business Intelligence. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470634431.

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Howson, Cindi. Successful Business Intelligence. New York: McGraw-Hill, 2008.

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1924-, Hussain Khateeb M., ed. Artificial intelligence and business management. Norwood, N.J: Ablex Pub. Corp., 1992.

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Shan, Caifeng. Video Analytics for Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Azevedo, Ana, and Manuel Filipe Santos. Integration of data mining in business intelligence systems. Hershey: Business Science Reference, 2015.

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Nancy, Williams, ed. The profit impact of business intelligence. Amsterdam: Elsevier/Morgan Kaufmann, 2007.

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Volitich, Dan. IBM Cognos 8 Business Intelligence. New York: McGraw-Hill, 2008.

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Book chapters on the topic "Business intelligence systems"

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems, 363–68. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_881.

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems, 287–88. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_881.

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Rizzi, Stefano. "Business Intelligence." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_881-2.

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Kale, Vivek. "Business Intelligence Systems." In Enterprise Performance Intelligence and Decision Patterns, 139–50. New York : CRC Press, [2017]: Auerbach Publications, 2017. http://dx.doi.org/10.4324/9781351228428-10.

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Caserio, Carlo, and Sara Trucco. "Business Intelligence Systems." In Contributions to Management Science, 43–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77679-8_3.

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Negash, Solomon, and Paul Gray. "Business Intelligence." In Handbook on Decision Support Systems 2, 175–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-48716-6_9.

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Gronwald, Klaus-Dieter. "BI: Business Intelligence." In Integrated Business Information Systems, 119–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-53291-1_13.

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Gronwald, Klaus-Dieter. "BI: Business Intelligence." In Integrated Business Information Systems, 81–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-59811-5_5.

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Kazeli, Hariklea. "Cloud Business Intelligence." In Business Information Systems Workshops, 307–17. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11460-6_26.

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Casati, Fabio, Umeshwar Dayal, and Ming-Chien Shan. "Business Operation Intelligence." In Databases in Networked Information Systems, 213–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36233-9_17.

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Conference papers on the topic "Business intelligence systems"

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Dasgupta, Supratim, and Vamsi Krishna Vankayala. "Developing Real Time Business Intelligence Systems the Agile Way." In 2007 1st Annual IEEE Systems Conference. IEEE, 2007. http://dx.doi.org/10.1109/systems.2007.374652.

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Krneta, Dragoljub, Dragica Radosav, and Biljana Radulovic. "Realization business intelligence in commerce using Microsoft Business Intelligence." In 2008 6th International Symposium on Intelligent Systems and Informatics (SISY 2008). IEEE, 2008. http://dx.doi.org/10.1109/sisy.2008.4664943.

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Mach, Maria Antonina, and M. Salem Abdel-Badeeh. "Intelligent techniques for business intelligence in healthcare." In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687209.

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Ramirez Ramirez, Margarita, Sergio Octavio Vazquez Nunez, Esperanza Manrique Rojas, and Hilda Beatriz Ramirez Moreno. "Business Intelligence and BigData." In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2019. http://dx.doi.org/10.23919/cisti.2019.8760628.

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Verma, Nitya, and Amy Voida. "Mythologies of Business Intelligence." In CHI'16: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2851581.2892379.

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Olszak, Celina M. "Towards an Understanding Business Intelligence. A Dynamic Capability-Based Framework for Business Intelligence." In 2014 Federated Conference on Computer Science and Information Systems. IEEE, 2014. http://dx.doi.org/10.15439/2014f68.

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Guarda, Teresa, Marcelo Leon, Maria Fernanda Augusto, Oscar Barrionuevo, Marjone Pesantes, Eduardo Pomboza, and Jorge Alvarez. "Business intelligence pervasive systems: BIPS model." In 2017 12th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2017. http://dx.doi.org/10.23919/cisti.2017.7975843.

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Hellsten, Pasi, and Jussi Myllärniemi. "Business Intelligence Process Model Revisited." In 11th International Conference on Knowledge Management and Information Systems. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0008354503410348.

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Singh, Nehul, and Satyendra Singh Chouhan. "Role of Artificial Intelligence for Development of Intelligent Business Systems." In 2021 IEEE International Symposium on Smart Electronic Systems (iSES). IEEE, 2021. http://dx.doi.org/10.1109/ises52644.2021.00092.

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Correia, Anacleto, Pedro B. Agua, and Afonso Luis. "Business Intelligence supporting Budget Management." In 2021 16th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2021. http://dx.doi.org/10.23919/cisti52073.2021.9476430.

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