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Relevant bibliographies by topics / Business intelligence

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Journal articles
Dissertations / Theses
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Academic literature on the topic 'Business intelligence'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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Journal articles on the topic "Business intelligence"

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Quijada, Carlos Alfonso. "Business intelligence." Realidad Empresarial, no. 9 (July 24, 2020): 45–48. http://dx.doi.org/10.5377/reuca.v0i9.10068.

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Las empresas que implementen a tiempo procesos de business intelligence con el fin de transformar los datos en información valiosa para tomar mejores decisiones tendrán una ventaja sobre sus competidores. Y quienes hagan caso omiso de esta tendencia corren el riesgo de quedarse rezagados y de hasta quedar fuera del mercado en el mediano plazo. Realidad Empresarial No. 9, 2020: 45-48

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Pinto Ferreira, Antonio Augusto, Natalia Talan Freitas Alves, Silvio Francisco Morgon, and Solange Pereira dos Santos. "BUSINESS INTELLIGENCE." SITEFA - Simpósio de Tecnologia da Fatec Sertãozinho 3, no. 1 (March 7, 2021): 268–74. http://dx.doi.org/10.33635/sitefa.v3i1.113.

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O conceito de Business Intelligence (BI) tem sido amplamente utilizado nas grandes empresas. São muitos os relatos de aumento de renda e redução de custos justificando o valor investido na implantação e manutenção das ferramentas e analistas necessários. Porém, a maior parte das empresas do Brasil é constituída por micro ou pequenas empresas e o conceito de BI não tem a mesma amplitude de utilização. Isso ocorre porque os recursos dessas empresas é limitado e o custo de um BI é alto. Utilizando a pesquisa bibliográfica e documental, este artigo mostra como as micro e pequenas empresas são caracterizadas e quais os benefícios e possíveis custos de implantação de um BI chegando à conclusão de que o custo é impeditivo para a implantação do conceito em micro empresas e na maior parte das empresas de pequeno porte.

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Post, Gerald V., and Albert Kagan. "Business Intelligence." International Journal of Business Intelligence Research 3, no. 3 (July 2012): 16–28. http://dx.doi.org/10.4018/jbir.2012070102.

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Data mining and business intelligence tools have been adding features and gaining uses, and statistical tools developed for data mining tasks often require advanced knowledge and training to apply. Development of these selected tools requires tradeoffs in ease of use and power. This study asks users to evaluate the various tools and attributes to identify the relative value of the various components and provide direction for improvements and new tools. Evaluating multi-attribute software is a challenging task, and this study provides a method of evaluating the data and analyzing tradeoffs. A structured equation model (SEM) is applied to the process. Each of the existing tools evaluated have different relative strengths, so it is important to match the organization’s primary tasks to the relative strengths of the tool.

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Chamoni, Peter, and Markus Linden. "Business Intelligence." WiSt - Wirtschaftswissenschaftliches Studium 40, no. 6 (2011): 276–81. http://dx.doi.org/10.15358/0340-1650-2011-6-276.

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Chandrasekhar, S. "Business Intelligence." Asia Pacific Business Review 1, no. 1 (January 2005): 84–88. http://dx.doi.org/10.1177/097324700500100110.

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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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Reinkemeyer, Lars, Markus Gallenberger, Marco Beria, Uwe Müller, and Tim Hahn. "Business Intelligence." Digitale Welt 3, no. 1 (December 11, 2018): 44–52. http://dx.doi.org/10.1007/s42354-019-0149-z.

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Beck, Chris. "Business Intelligence." Manufacturing Management 2020, no. 1 (January 2020): 34–35. http://dx.doi.org/10.12968/s2514-9768(22)90109-7.

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Yermish, Ira, Virginia Miori, John Yi, Rashmi Malhotra, and Ronald Klimberg. "Business Plus Intelligence Plus Technology Equals Business Intelligence." International Journal of Business Intelligence Research 1, no. 1 (January 2010): 48–63. http://dx.doi.org/10.4018/jbir.2010071704.

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In this article the authors will show how the parallel developments of information technology at the operational business level and decision support concepts progressed through the decades of the twentieth century with only minimal success at strategic application. They will posit that the twin technological developments of the world-wide-web and very inexpensive mass storage provided the environment to facilitate the convergence of business operations and decision support into the strategic application of business intelligence.

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Dissertations / Theses on the topic "Business intelligence"

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Хмелик, Людмила Яківна, Людмила Яковлевна Хмелик, Liudmyla Yakivna Khmelyk, and R. O. Atamanyuk. "Business intelligence." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/13506.

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Strejčková, Lucie. "Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124609.

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The diploma project deals with the issue of Business Intelligence, it focuses on tools used for data analysis and presentation. The project is divided into two parts -- the theoretical and practical one. The theoretical one applies to the characterization of the principle, the description of the architecture components and presentation techniques. The aim of this project is to suggest new suitable analytical tools and graphic interface of BI system for small and medium-sized businesses. Using selected tools is illustrated on a specific example.

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Bolton, Björn, and Axel Jakobsson. "Business Intelligence: Transforming Intelligence into Actions." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-354890.

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Business Intelligence (BI) is a topic that has attracted attention from both researchers and practitioners. Despite BI's promising possibilities, few organizations are able to transform BI-insights into actions. Thus, the purpose of this study was to understand: How organizations can transform BI insights into actions, and which capabilities impact this transformation. In order to obtain this understanding, a case-study was conducted. We interviewed six consultants from leading consultancy firms, and a practitioner who uses BI on a daily basis. Prior to this, the authors reviewed previous BI literature which suggests that BI needs to be combined with capabilities for employees to utilize BI. Microfoundations was used as a theoretical framework to identify important capabilities and how they relate to BI. The findings distinguished specific capabilities that impacts the ability to utilize BI. Capabilities such as communication, sponsorship, culture, and clear strategies & goals, are important in order to better take advantage of BI. The conclusions are that hard skills (e.g. technical competencies), education and experience among the employees may not be as crucial as previously thought. This is because BI-systems are becoming more intuitive and easier to use.

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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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Sklenář, Ondřej. "Nástroje Business Intelligence - analýza trhu nástrojů Self-service Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-192447.

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The diploma thesis is focused on a specific area of self-service business intelligence. The advantage of this approach to the business intelligence is reduction of demands on IT development and using tools by end users. They can generate reports and outputs according to their requirements during the relevant time period. The theoretical part is dedicated to illustrate this concept with all benefits and risks. Furthermore, it describes trends occurring in the domain of business intelligence. These trends transcend outline the domain of business intelligence and are valid throughout IT. The practical part is dedicated to the analysis market of self-service business intelligence tools. On basis of established criteria are then compared these tools and deduced general conclusions regarding their functionality. Then, by using three selected tools is created comprehensive business intelligence task with the aim of clarifying a degree of self-service for these instruments. The main benefit of this thesis is based in the integrated analysis of market self-service business intelligence tools and determination of their functionality.

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Slebodník, Matej. "Implementace Business Intelligence." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2021. http://www.nusl.cz/ntk/nusl-444688.

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The diploma thesis deals with the implementation of a Business Intelligence solution for the endowment fund helping with debt relief for people and thus replaces the current process of manually created reports. The main goal of this solution is to bring to the endowment fund the opportunity to make faster and better decisions, as well as many other benefits associated with Business Intelligence.

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Bľanda, Lukáš. "Implementácia Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-17181.

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This diploma thesis deals with the implementation of Business Intelligence solution in a travel industry company and its interconnection to Balanced Scorecard as one of the enterprise performance management tool. First part focuses on pointing out the main theoretical foundations of Balanced Scorecard and Business Intelligence. It describes Balanced Scorecard and its principles and it also defines Business Intelligence, the architecture of BI and the implementation process generally. In the second part the particular metrics model is generated and a few specific metrics from this model are implemented in the Business Intelligence pilot project.

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Křižka, Radek. "Mobilní Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-150094.

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Business Intelligence (BI) has now become a core part to many businesses due to the benefits it brings -- the ability to access data in a common format from multiple sources and making decisions that help organization to move closer to its goals. Many workers today spend most of their time away from their office and can't easily access corporate data. The use of the Internet on mobile devices has changed the way people consume information. Embracing mobile computing means having the ability to access information anywhere, anytime and as a result consumers can make decisions faster. Thesis is focused on mobile Business Intelligence and the aim is to provide o comprehensive overview of this area, examine market trends, define critical success factors for implementation projects, and introduce mobile BI platform QlikView. Furthermore it explains the differences between traditional and mobile BI, explores benefits and drawbacks of these tools and the challenges that must be addressed. The reader will learn what types of employees and tasks are suited for mobile BI programs and outlined critical success factors might be valuable information for any company planning implementation of mobile BI tools.

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Dzimko, Miroslav. "Řešení Business Intelligence." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318585.

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Diploma thesis presents an evaluation of the current state of the company system, identification of critical areas and areas suitable for improvement. Based on the theoretical knowledge and analysis results, commercial Business Intelligence software is designed to enhance the quality and efficiency of the company's decision-support system and the introduction of an advanced Quality Culture system. The thesis reveals critical locations in the corporate environment and opens up space to design improvements to the system.

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Turricchia, Elisa <1984&gt. "Pervasive Business Intelligence." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5232/1/TURRICCHIA_ELISA_TESI.pdf.

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In the last few years, a new generation of Business Intelligence (BI) tools called BI 2.0 has emerged to meet the new and ambitious requirements of business users. BI 2.0 not only introduces brand new topics, but in some cases it re-examines past challenges according to new perspectives depending on the market changes and needs. In this context, the term pervasive BI has gained increasing interest as an innovative and forward-looking perspective. This thesis investigates three different aspects of pervasive BI: personalization, timeliness, and integration. Personalization refers to the capacity of BI tools to customize the query result according to the user who takes advantage of it, facilitating the fruition of BI information by different type of users (e.g., front-line employees, suppliers, customers, or business partners). In this direction, the thesis proposes a model for On-Line Analytical Process (OLAP) query personalization to reduce the query result to the most relevant information for the specific user. Timeliness refers to the timely provision of business information for decision-making. In this direction, this thesis defines a new Data Warehuose (DW) methodology, Four-Wheel-Drive (4WD), that combines traditional development approaches with agile methods; the aim is to accelerate the project development and reduce the software costs, so as to decrease the number of DW project failures and favour the BI tool penetration even in small and medium companies. Integration refers to the ability of BI tools to allow users to access information anywhere it can be found, by using the device they prefer. To this end, this thesis proposes Business Intelligence Network (BIN), a peer-to-peer data warehousing architecture, where a user can formulate an OLAP query on its own system and retrieve relevant information from both its local system and the DWs of the net, preserving its autonomy and independency.

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Books on the topic "Business intelligence"

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Werther, Iron. Business Intelligence. München: Carl Hanser Verlag GmbH & Co. KG, 2013. http://dx.doi.org/10.3139/9783446436350.

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Skyrius, Rimvydas. Business Intelligence. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67032-0.

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Fakir, Mohamed, Mohamed Baslam, and Rachid El Ayachi, eds. Business Intelligence. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76508-8.

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Fakir, Mohamed, Mohamed Baslam, and Rachid El Ayachi, eds. Business Intelligence. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06458-6.

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Zimányi, Esteban, ed. Business Intelligence. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05461-2.

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Cohen, Corine. Business Intelligence. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557648.

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Zimányi, Esteban, and Ralf-Detlef Kutsche, eds. Business Intelligence. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17551-5.

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Aufaure, Marie-Aude, and Esteban Zimányi, eds. Business Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27358-2.

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Marcel, Patrick, and Esteban Zimányi, eds. Business Intelligence. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61164-8.

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Zimányi, Esteban, and Alberto Abelló, eds. Business Intelligence. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39243-1.

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Book chapters on the topic "Business intelligence"

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Cole, Tim. "Intelligent Business statt Business Intelligence." In Erfolgsfaktor Künstliche Intelligenz, 15–52. München: Carl Hanser Verlag GmbH & Co. KG, 2020. http://dx.doi.org/10.3139/9783446465398.001.

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Niu, Li, Jie Lu, and Guangquan Zhang. "Business Intelligence." In Cognition-Driven Decision Support for Business Intelligence, 19–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03208-0_2.

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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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Burmester, Lars. "Business Intelligence." In Adaptive Business-Intelligence-Systeme, 109–46. Wiesbaden: Vieweg+Teubner, 2011. http://dx.doi.org/10.1007/978-3-8348-8118-2_5.

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Garrett, Rob. "Business Intelligence." In Pro SharePoint 2013 Administration, 427–62. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-4942-9_12.

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Gray, Paul. "Business Intelligence." In Encyclopedia of Operations Research and Management Science, 132–39. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_1179.

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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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Millham, Richard, Israel Edem Agbehadji, and Emmanuel Freeman. "Business Intelligence." In Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing, 207–18. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6695-0_11.

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Nikolik, Dragan. "Business Intelligence." In A Manager’s Primer on e-Networking, 246–61. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-007-0862-4_17.

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Alff, Sascha C., and Winfried Hungert. "Business Intelligence." In Innovation durch Geschäftsprozessmanagement, 155–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17138-3_12.

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Conference papers on the topic "Business intelligence"

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de Carvalho, Duarte, Ricardo Rocha, Vanessa Fernandes, and Sofia Neves. "Business Intelligence." In the Ninth International C* Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2948992.2949011.

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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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Wu, Jui-Yu. "Computational Intelligence-Based Intelligent Business Intelligence System: Concept and Framework." In 2010 Second International Conference on Computer and Network Technology. IEEE, 2010. http://dx.doi.org/10.1109/iccnt.2010.23.

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Li, Kin Fun. "Internet Business Intelligence." In 2010 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC). IEEE, 2010. http://dx.doi.org/10.1109/3pgcic.2010.45.

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Helfenstein, Sacha, Olena Kaikova, Oleksiy Khriyenko, and Vagan Terziyan. "Emotional Business Intelligence." In 2014 7th International Conference on Human System Interactions (HSI). IEEE, 2014. http://dx.doi.org/10.1109/hsi.2014.6860441.

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Mazón, Jose-Norberto, Jose Jacobo Zubcoff, Irene Garrigós, Roberto Espinosa, and Rolando Rodríguez. "Open business intelligence." In the 2012 Joint EDBT/ICDT Workshops. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2320765.2320812.

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Su, Jianwen, and Yan Tang. "Business Intelligence Revisited." In 2017 Fifth International Conference on Advanced Cloud and Big Data (CBD). IEEE, 2017. http://dx.doi.org/10.1109/cbd.2017.9.

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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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Brichni, Manel, Sophie Dupuy-Chessa, Lilia Gzara, Nadine Mandran, and Corinne Jeannet. "Business intelligence for Business Intelligence: A case study at STMicroelectronics." In 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS). IEEE, 2015. http://dx.doi.org/10.1109/rcis.2015.7128885.

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FOTACHE, Doina, Ionuţ Daniel ANASTASIEI, and Vasile-Daniel PĂVĂLOAIA. "BUSINESS PERFORMANCE DECISIONS BY SOCIAL BUSINESS INTELLIGENCE." In 18th International Conference on INFORMATICS in ECONOMY. Education, Research and Business Technologies. Bucharest University of Economic Studies Press, 2019. http://dx.doi.org/10.12948/ie2019.04.12.

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Reports on the topic "Business intelligence"

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Kramer, Mitchell. Oracle Business Intelligence. Boston, MA: Patricia Seybold Group, March 2002. http://dx.doi.org/10.1571/pr3-8-02cc.

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Amekedzi, Komivi. Using Business Intelligence Tools to Make Data-Driven Decisions. Ames (Iowa): Iowa State University, January 2021. http://dx.doi.org/10.31274/cc-20240624-1554.

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Nduka, Williams. The Significance of Artificial Intelligence in Business Process Management. Ames (Iowa): Iowa State University, December 2023. http://dx.doi.org/10.31274/cc-20240624-1492.

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Shakya, Parash. Role of business intelligence and information technology in developing countries. Ames (Iowa): Iowa State University, January 2019. http://dx.doi.org/10.31274/cc-20240624-1243.

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Schacher, Gordon, Nelson Irvine, and Roger B. Hoyt. Joint Intelligence Operations Center (JIOC) Baseline Business Process Model & Capabilities Evaluation Methodology. Fort Belvoir, VA: Defense Technical Information Center, March 2012. http://dx.doi.org/10.21236/ada562584.

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Redmond-Neal, Amanda Lee. Business intelligence for human resources. Toward a new paradigm for report development and delivery. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1173186.

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Cao, Larry. Handbook of Artificial Intelligence and Big Data Applications in Investments. CFA Institute, March 2023. http://dx.doi.org/10.56227/23.1.5.

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Learn how asset managers are leveraging data science to garner investment insights, build more resilient portfolios, make better trading decisions, streamline client services, develop client-centric products, and gather business intelligence.

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Vuyyuru, Tejaswini. Using Predictive Maintenance techniques and Business Intelligence to develop smarter factory systems for the digital age. Ames (Iowa): Iowa State University, January 2018. http://dx.doi.org/10.31274/cc-20240624-1566.

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Rapp, Jeffrey N. Intelligence Requirements for Military Operations Other Than War: A Low Technology Business, Now and In the Future. Fort Belvoir, VA: Defense Technical Information Center, March 1998. http://dx.doi.org/10.21236/ada342276.

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Pérez Del Barrio, Amaia, Pablo Menéndez Fernández-Miranda, Pablo Sanz Bellón, Enrique Marqués Fraguela, and Enrique Marco De Lucas. Problemas con la Descripción de los Estudios en los Sistemas de Gestión de Dosis: Soluciones con Herramientas de Business Intelligence (BI). Peeref, October 2022. http://dx.doi.org/10.54985/peeref.2210p2627066.

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