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Статті в журналах з теми "Business intelligence Software"
CRISTESCU, Marian Pompiliu. "Traditional Enterprise Business Intelligence Software Compared to Software as a Service Business Intelligence." Informatica Economica 20, no. 1/2016 (March 30, 2016): 39–47. http://dx.doi.org/10.12948/issn14531305/20.1.2016.04.
Повний текст джерелаPost, 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.
Повний текст джерелаBimonte, Sandro, Michel Schneider, and Omar Boussaid. "Business Intelligence Indicators." International Journal of Data Warehousing and Mining 12, no. 4 (October 2016): 75–98. http://dx.doi.org/10.4018/ijdwm.2016100104.
Повний текст джерелаČižman, Anton, and Janko Černetič. "Improving Manufacturing Efficiency with Business Intelligence Software." IFAC Proceedings Volumes 30, no. 24 (September 1997): 153–56. http://dx.doi.org/10.1016/s1474-6670(17)42246-4.
Повний текст джерелаMaté, Alejandro, Juan Trujillo, Félix García, Manuel Serrano, and Mario Piattini. "Empowering global software development with business intelligence." Information and Software Technology 76 (August 2016): 81–91. http://dx.doi.org/10.1016/j.infsof.2016.04.011.
Повний текст джерелаChugh, Ritesh, and Srimannarayana Grandhi. "Why Business Intelligence?" International Journal of E-Entrepreneurship and Innovation 4, no. 2 (April 2013): 1–14. http://dx.doi.org/10.4018/ijeei.2013040101.
Повний текст джерелаBanica, Logica, Liviu Cristian Stefan, and Mariana Jurian. "Business Intelligence For Educational Purpose." Balkan Region Conference on Engineering and Business Education 1, no. 1 (August 15, 2014): 333–38. http://dx.doi.org/10.2478/cplbu-2014-0049.
Повний текст джерелаMendoza, Rubén A. "Business Intelligence 2.0." International Journal of Business Intelligence Research 1, no. 4 (October 2010): 63–76. http://dx.doi.org/10.4018/jbir.2010100104.
Повний текст джерелаTofan, Dragoş Ovidiu. "Business Intelligence Security." Review of Economic and Business Studies 9, no. 1 (June 1, 2016): 157–69. http://dx.doi.org/10.1515/rebs-2016-0030.
Повний текст джерелаASLAN, İpek, Aşkın DEMİRAG, and Erkut AKKARTAL. "Collaboration of Business Intelligence and Cloud Computing and Selecting the Best Cloud Business Intelligence Solution." AJIT-e Online Academic Journal of Information Technology 12, no. 46 (August 28, 2021): 29–45. http://dx.doi.org/10.5824/ajite.2021.03.002.x.
Повний текст джерелаДисертації з теми "Business intelligence Software"
VENKATESH, UMA DEVI. "LITERATURE REVIEW ON BUSINESS INTELLIGENCE : BUSINESS INTELLIGENCE SOFTWARE FOR EDUCATIONAL INSTITUTIONS." Thesis, Högskolan i Halmstad, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-33523.
Повний текст джерелаKang, Jian. "Automating business intelligence recovery in software evolution." Thesis, De Montfort University, 2009. http://hdl.handle.net/2086/2414.
Повний текст джерелаSabanovic, Adis. "Business Intelligence Software Customers’ Understanding, Expectations and Needs." Thesis, Kristianstad University College, School of Health and Society, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-4707.
Повний текст джерелаModern companies operate in incredibly complex and dynamic environments. This is clearly characterized by constant changes in technology and in various market forces as well as by enormous amounts of data and information that need to be gathered and analyzed every day. Governmental regulations and ongoing competitor pressures, among other external and internal factors, are issues that managers and decision makers in a company must take into a consideration when making decisions. The need for BI systems is growing stronger and businesses in various industries demand such tools that will help them stay on the edge in order to be competitive. Hence the purpose of this paper is to find out what their companies desire when choosing a BI system to work with. What are their needs and what do they expect and understand from this technological system that will hopefully make them work easier and gain their knowledge about the business they operate in.
A web questionnaire is aimed at 67 Swedish companies from various industries and the answers have been summarized and analyzed in different cross tables for comparison reasons. Respondents from the Manufacturing industry were those with the highest response rate. A model called The PET-model of BI implementation was created, as a result of the theoretical findings, and this model is used to finalize the results and the conclusions of this paper.
Adelakun, Olawale, and Thomas Kemper. "Software-as-a-Service Business Intelligence : Adoption Criteria and Business Value." Thesis, Jönköping University, JIBS, Business Informatics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-12963.
Повний текст джерелаThe area of Business Intelligence (BI) is both broad and multifaceted and is becoming an increasingly pervasive tool utilized within organizations allowing them to gain greater insight into their business operations as well as well as the way in which their customers interact with them. By enabling businesses to perform powerful, effective analytics and reporting, BI tools allow them to maximize use of their data and facilitate better planning, forecasting and the ability to have a more targeted and efficient value chain. Usage of BI tools allow organizations to not only achieve but leverage their competitive advantage. SMEs are no different in their pursuit for competitive advantage and market share but often is the case that they lack the resources in order to make the substantial investments into the software and infrastructure required to host a solution on-premise. The Software-as-a-Service (SaaS) model of allowing users to have access to powerful tools and services without having to purchase the solutions or the infrastructure needed to host it on-premise allows SMEs an ideal opportunity to perform many or all of the functionalities that on-premise BI provides. SaaS BI is a relatively new concept only a few years old, but improvements in functionality and features, reliability of service levels and lower costs are allowing it to gain traction and it is projected to increase its momentum in the next few years. The aim of this paper is to investigate the factors that lead to adoption/non-adoption, assigned importance and perceived business value of SaaS BI within SMEs. These issues will be addressed through identification of the key decision criteria that influence SMEs to adopt SaaS BI solutions over an on-premise solution and vice versa. Greater insight into the decision making process, usage and value will be investigated with the cooperation of two vendors within the BI field. A two pronged approach targeting both SaaS and on-premise BI vendors and the users is adopted in order to find out the perspective on either end and whether or not they are incongruent. Semi-structured interviews were targeted at both an on-premise vendor and a SaaS vendor and their customers. A questionnaire was deployed to clients of both these vendors. Analysis was then conducted on the findings using an integrated selection model encompassing BI and SaaS theories and concepts outlined in the paper.
Filipčík, Zdeněk. "Nástroje Business Intelligence jako Open Source." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-150123.
Повний текст джерелаGluchowski, Peter, Marcus Hofmann, Frieder Jacobi, Robert Krawatzeck, and André Müller. "Business-Intelligence-Umfrage 2011: Softwaregestütztes Lebenszyklusmanagement und aktuelles Dokumentationsgeschehen für Business-Intelligence-Systeme." Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-75452.
Повний текст джерелаSlavětínský, Radek. "Analýza cloudových řešení Business Intelligence pro SME." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-358847.
Повний текст джерелаBashir, Yusuf. "Next generation business intelligence software, areas for growth & opportunities for innovation." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65795.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (p. 54-55).
In today's world, as the volume of business and consumer data continues to grow at an unprecedented pace, there is increasing desire to utilize that data in new and innovative and ways to provide insight and improve decision making. For businesses, data is being generated from transactions, machine logs, digital media and feeds from sensors and wireless devices at a volume and velocity not seen before. When combined with data from external sources such as partners, or from the Internet from blogs, social networking sites, YouTube, Facebook and Twitter, it has the capability to provide organizations with new insight, a more holistic picture of customer and stakeholder behavior and new ways of gaining competitive advantage. Consumers are being presented with applications of increasing analytical sophistication, leading to growing comfort in making fact-based decisions. New devices will help monitor energy usage within the home and provide insight on the optimal times to schedule devices and run household appliances. As data volumes continue to grow, systems will need to automate the uncovering of patterns and trends in data if they are to scale. Business Intelligence (BI) software, which has traditionally been used to gain insight from data, will need to evolve and new capabilities developed to support these significant changes. Areas of growth and opportunities for new innovation within the BI software industry will be explored that will enable stakeholders to take full advantage of this new and exciting opportunity.
by Yusuf Bashir.
S.M.
Gina, Bonginkosi Phila. "Factors That Drive the Selection of Business Intelligence Tools in South African Financial Services Providers." Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/33741.
Повний текст джерелаSantos, Igor Peterson Oliveira. "Um framework de testes unitários para procedimentos de carga em ambientes de business intelligence." Universidade Federal de Sergipe, 2016. http://ri.ufs.br:8080/xmlui/handle/123456789/3390.
Повний текст джерелаBusiness Intelligence (BI) relies on Data Warehouse (DW), a historical data repository designed to support the decision making process. Despite the potential benefits of a DW, data quality issues prevent users from realizing the benefits of a BI environment and Data Analytics. Problems related to data quality can arise in any stage of the ETL (Extract, Transform and Load) process, especially in the loading phase. This thesis presents an approach to automate the selection and execution of previously identified test cases for loading procedures in BI environments and Data Analytics based on DW. To verify and validate the approach, a unit test framework was developed. The overall goal is achieve data quality improvement. The specific aim is reduce test effort and, consequently, promote test activities in DW process. The experimental evaluation was performed by two controlled experiments in the industry. The first one was carried out to investigate the adequacy of the proposed method for DW procedures development. The Second one was carried out to investigate the adequacy of the proposed method against a generic framework for DW procedures development. Both results showed that our approach clearly reduces test effort and coding errors during the testing phase in decision support environments.
A qualidade de um produto de software está diretamente relacionada com os testes empregados durante o seu desenvolvimento. Embora os processos de testes para softwares aplicativos e sistemas transacionais já apresentem um alto grau de maturidade, estes devem ser investigados para os processos de testes em um ambiente de Business Intelligence (BI) e Data Analytics. As diferenças deste ambiente em relação aos demais tipos de sistemas fazem com que os processos e ferramentas de testes existentes precisem ser ajustados a uma nova realidade. Neste contexto, grande parte das aplicações de Business Intelligence (BI) efetivas depende de um Data Warehouse (DW), um repositório histórico de dados projetado para dar suporte a processos de tomada de decisão. São as cargas de dados para o DW que merecem atenção especial relativa aos testes, por englobar procedimentos críticos em relação à qualidade. Este trabalho propõe uma abordagem de testes, baseada em um framework de testes unitários, para procedimentos de carga em um ambiente de BI e Data Analytics. O framework proposto, com base em metadados sobre as rotinas de carga, realiza a execução automática de casos de testes, por meio da geração de estados iniciais e a análise dos estados finais, bem como seleciona os casos de testes a serem aplicados. O objetivo é melhorar a qualidade dos procedimentos de carga de dados e reduzir o tempo empregado no processo de testes. A avaliação experimental foi realizada através de dois experimentos controlados executados na indústria. O primeiro avaliou a utilização de casos de testes para as rotinas de carga, comparando a efetividade do framework com uma abordagem manual. O segundo experimento efetuou uma comparação com um framework genérico e similar do mercado. Os resultados indicaram que o framework pode contribuir para o aumento da produtividade e redução dos erros de codificação durante a fase de testes em ambientes de suporte à decisão.
Книги з теми "Business intelligence Software"
Czernicki, Bart. Silverlight 4 Business Intelligence Software. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8.
Повний текст джерелаservice), SpringerLink (Online, ed. Silverlight 4 Business Intelligence Software. Berkeley, CA: Bart Czernicki, 2010.
Знайти повний текст джерелаSorensen, Dean. Business performance intelligence software: A market evaluation. Morristown, NJ]: Financial Executives Research Foundation, 2003.
Знайти повний текст джерелаservice), SpringerLink (Online, ed. Next-Generation Business Intelligence Software with Silverlight 3. Berkeley, CA: Apress, 2010.
Знайти повний текст джерелаCzernicki, Bart. Next-Generation Business Intelligence Software with Silverlight 3. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2488-4.
Повний текст джерелаIntelligent agent software engineering. Hershey, PA: Idea Group Pub., 2003.
Знайти повний текст джерелаDecision support systems for business intelligence. 2nd ed. Hoboken, N.J: Wiley, 2010.
Знайти повний текст джерелаVolitich, Dan. IBM Cognos 8 Business Intelligence. New York: McGraw-Hill, 2008.
Знайти повний текст джерелаShafer, Dan. Designing intelligent front ends for business software. New York: Wiley, 1989.
Знайти повний текст джерелаBouthillier, France. Assessing competitive intelligence software: A guide to evaluating CI technology. Medford, N.J: Information Today, 2003.
Знайти повний текст джерелаЧастини книг з теми "Business intelligence Software"
Czernicki, Bart. "Mobile Intelligence." In Silverlight 4 Business Intelligence Software, 391–421. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_12.
Повний текст джерелаCzernicki, Bart. "Business Intelligence 2.0 Defined." In Silverlight 4 Business Intelligence Software, 1–25. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_1.
Повний текст джерелаCzernicki, Bart. "Applying Collective Intelligence." In Silverlight 4 Business Intelligence Software, 251–81. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_8.
Повний текст джерелаCzernicki, Bart. "Integrating with Business Intelligence Systems." In Silverlight 4 Business Intelligence Software, 367–89. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_11.
Повний текст джерелаCzernicki, Bart. "Business Intelligence 2.0 Defined." In Next-Generation Business Intelligence Software with Silverlight 3, 1–26. Berkeley, CA: Apress, 2009. http://dx.doi.org/10.1007/978-1-4302-2488-4_1.
Повний текст джерелаCzernicki, Bart. "Enhancing Visual Intelligence in Silverlight." In Silverlight 4 Business Intelligence Software, 219–50. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_7.
Повний текст джерелаCzernicki, Bart. "Surfacing Silverlight Business Intelligence in SharePoint." In Silverlight 4 Business Intelligence Software, 423–42. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_13.
Повний текст джерелаCzernicki, Bart. "Silverlight as a Business Intelligence Client." In Silverlight 4 Business Intelligence Software, 53–96. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_3.
Повний текст джерелаCzernicki, Bart. "Adding Interactivity to Business Intelligence Data." In Silverlight 4 Business Intelligence Software, 97–134. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3061-8_4.
Повний текст джерелаCzernicki, Bart. "Integrating with Business Intelligence Systems." In Next-Generation Business Intelligence Software with Silverlight 3, 367–93. Berkeley, CA: Apress, 2009. http://dx.doi.org/10.1007/978-1-4302-2488-4_11.
Повний текст джерелаТези доповідей конференцій з теми "Business intelligence Software"
Ouf, Shimaa, Mona Nasr, Mohamed Amr, Mohamed Mosaad, Khaled Kamal, Fatma Mostafa, Rehab Said, and Sherook Mohamed. "Business intelligence software as a service (SAAS)." In 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN). IEEE, 2011. http://dx.doi.org/10.1109/iccsn.2011.6014350.
Повний текст джерелаBaransel, Ayse Eser, and Cesur Baransel. "Architecturing Business Intelligence for SMEs." In 2012 IEEE 36th Annual Computer Software and Applications Conference - COMPSAC 2012. IEEE, 2012. http://dx.doi.org/10.1109/compsac.2012.82.
Повний текст джерелаOuf, Shimaa, and Mona Nasr. "Business Intelligence in the Cloud." In 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN). IEEE, 2011. http://dx.doi.org/10.1109/iccsn.2011.6014351.
Повний текст джерелаMcAllister, Michael. "Success factors of Business Intelligence." In 2009 6th IEEE International Working Conference on Mining Software Repositories. MSR 2009. IEEE, 2009. http://dx.doi.org/10.1109/msr.2009.5069473.
Повний текст джерела"AGENTS FOR MANAGING BUSINESS-TO-BUSINESS INTERACTIONS - Software Agents for Managing Business-to-Business Collaborations." In 3rd International Conference on Agents and Artificial Intelligence. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003180002380244.
Повний текст джерелаTuncer, Isilay, Sevval Az, Askin Karakas, and Mehmet Gokturk. "Context-Based Corporate Business Intelligence Assistant." In 2019 1st International Informatics and Software Engineering Conference (UBMYK). IEEE, 2019. http://dx.doi.org/10.1109/ubmyk48245.2019.8965648.
Повний текст джерелаHans, Robert T., and Ernest Mnkandla. "Modeling software engineering projects as a business: A business intelligence perspective." In AFRICON 2013. IEEE, 2013. http://dx.doi.org/10.1109/afrcon.2013.6757849.
Повний текст джерелаKang, Jian, Jianjun Pu, Jianchu Huang, Zihou Zhou, and Hongji Yang. "Business Intelligence Recovery from Legacy Code." In 2008 32nd Annual IEEE International Computer Software and Applications Conference. IEEE, 2008. http://dx.doi.org/10.1109/compsac.2008.35.
Повний текст джерелаPuder, Arno, and Thomas Odenwald. "Augmenting Smart Items With Business Intelligence." In 2007 2nd International Conference on Communication Systems Software and Middleware. IEEE, 2007. http://dx.doi.org/10.1109/comswa.2007.382480.
Повний текст джерелаChen, Qiming, Parvathi Chundi, Umeshwar Dayal, and Meichun Hsu. "Dynamic software agents for business intelligence applications (poster)." In the second international conference. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/280765.280893.
Повний текст джерела