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Artículos de revistas sobre el tema "Business intelligence"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 29 de julio de 2024

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1

Quijada, Carlos Alfonso. "Business intelligence". Realidad Empresarial, n.º 9 (24 de julio de 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 y Solange Pereira dos Santos. "BUSINESS INTELLIGENCE". SITEFA - Simpósio de Tecnologia da Fatec Sertãozinho 3, n.º 1 (7 de marzo de 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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3

Post, Gerald V. y Albert Kagan. "Business Intelligence". International Journal of Business Intelligence Research 3, n.º 3 (julio de 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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4

Chamoni, Peter y Markus Linden. "Business Intelligence". WiSt - Wirtschaftswissenschaftliches Studium 40, n.º 6 (2011): 276–81. http://dx.doi.org/10.15358/0340-1650-2011-6-276.

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5

Chandrasekhar, S. "Business Intelligence". Asia Pacific Business Review 1, n.º 1 (enero de 2005): 84–88. http://dx.doi.org/10.1177/097324700500100110.

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Grünwald, Markus y Dirk Taubner. "Business Intelligence". Informatik-Spektrum 32, n.º 5 (27 de agosto de 2009): 398–403. http://dx.doi.org/10.1007/s00287-009-0374-1.

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7

Herring, Jan P. "Business Intelligence". Journal of Business Strategy 14, n.º 3 (marzo de 1993): 10–12. http://dx.doi.org/10.1108/eb039552.

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Reinkemeyer, Lars, Markus Gallenberger, Marco Beria, Uwe Müller y Tim Hahn. "Business Intelligence". Digitale Welt 3, n.º 1 (11 de diciembre de 2018): 44–52. http://dx.doi.org/10.1007/s42354-019-0149-z.

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9

Beck, Chris. "Business Intelligence". Manufacturing Management 2020, n.º 1 (enero de 2020): 34–35. http://dx.doi.org/10.12968/s2514-9768(22)90109-7.

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10

Yermish, Ira, Virginia Miori, John Yi, Rashmi Malhotra y Ronald Klimberg. "Business Plus Intelligence Plus Technology Equals Business Intelligence". International Journal of Business Intelligence Research 1, n.º 1 (enero de 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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11

Becker, Wolfgang, Kristin Kollacks y Patrick Ulrich. "ZP-Stichwort: Business Intelligence und Business Intelligence-Tools". Zeitschrift für Planung & Unternehmenssteuerung 21, n.º 2 (11 de marzo de 2010): 223–32. http://dx.doi.org/10.1007/s00187-010-0091-6.

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12

Kejriwal, Mudit. "Review on Business Intelligence Tools". International Journal of Psychosocial Rehabilitation 24, n.º 1 (20 de enero de 2020): 1770–74. http://dx.doi.org/10.37200/ijpr/v24i1/pr200277.

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13

Ahmed, Emad. "Utilization of Business Intelligence Tools among Business Intelligence Users". International Journal for Innovation Education and Research 9, n.º 6 (1 de junio de 2021): 237–53. http://dx.doi.org/10.31686/ijier.vol9.iss6.3172.

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The study was an investigation of the impact of perceived usefulness and perceived ease of use of business intelligence (BI) tools among users. The relationship between and among the dependent variable (utilization of BI tools) and the independent variables (perceived usefulness and perceived ease of use) was investigated through the lenses of technology acceptance model (TAM). Other objectives for the current research were to build a model to predict users’ utilization of the independent variables, and to generalize the results of the research to the IT population. Data for the current research was collected utilizing a survey questionnaire, designed by the researcher, with a 5-point Likert scale to interpret responses to the survey questions. The analysis consisted of descriptive statistics and multiple regressions models. A prediction model was structured using generalized linear models. The result of the study was the development of a prediction model for BI tools utilization through the lenses of a technology acceptance model (TAM). The model highlighted the importance of up-to-date information provided by current BI tools, ability of BI tools to provide users with more analytical tools to accomplish their jobs, the degree to which BI tools allow users to present convincing arguments, the ability of BI tools to provide users with more possible solutions, the ability of BI tools to reduce the time required to accomplish jobs, and the ability of BI tools to help users make relevant business predictions.

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14

Ortiz, Gustavo A. "Business Intelligence or Intelligent Business?" Computer Science and Information Technology 2, n.º 4 (abril de 2014): 192–96. http://dx.doi.org/10.13189/csit.2014.020402.

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15

Ranjan, Jayanthi. "Business justification with business intelligence". VINE 38, n.º 4 (24 de octubre de 2008): 461–75. http://dx.doi.org/10.1108/03055720810917714.

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16

Ereth, Julian y Hans-Georg Kemper. "Business Analytics und Business Intelligence". Controlling 28, n.º 8-9 (2016): 458–64. http://dx.doi.org/10.15358/0935-0381-2016-8-9-458.

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17

Mashingaidze, Sivave. "Harmonizing intelligence terminologies in business: Literature review". Journal of Governance and Regulation 3, n.º 4 (2014): 156–62. http://dx.doi.org/10.22495/jgr_v3_i4_c1_p8.

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The principal objective of this article is to do a literature review of different intelligence terminology with the aim of establishing the common attributes and differences, and to propose a universal and comprehensive definition of intelligence for common understanding amongst users. The findings showed that Competitive Intelligence has the broadest scope of intelligence activities covering the whole external operating environment of the company and targeting all levels of decision-making for instance; strategic intelligence, tactical intelligence and operative intelligence. Another terminology was found called Cyber IntelligenceTM which encompasses competitor intelligence, strategic intelligence, market intelligence and counterintelligence. In conclusion although CI has the broadest scope of intelligence and umbrella to many intelligence concepts, still Business Intelligence, and Corporate Intelligence are often used interchangeably as CI.

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18

ElMalah, Khaled y Mona Nasr. "Cloud Business Intelligence". International Journal of Advanced Networking Applications 10, n.º 06 (2019): 4120–24. http://dx.doi.org/10.35444/ijana.2019.100612.

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19

Chugh, Ritesh y Srimannarayana Grandhi. "Why Business Intelligence?" International Journal of E-Entrepreneurship and Innovation 4, n.º 2 (abril de 2013): 1–14. http://dx.doi.org/10.4018/ijeei.2013040101.

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Business Intelligence (BI) is one of the fastest growing software sector and software vendors are rapidly developing multiple BI tools to support the growing data analysis needs of organisations. In order to be sustainable in a briskly changing turbulent environment, organisations need to have access to information about their operational performance. BI tools play a vital role in supporting the decision makers at different organisational levels. As these tools are becoming critical in decision making, it has become not only an information technology concern but also a management concern. Without proper governance it would be impractical to achieve the value that BI tools offer. Adopting a BI governance framework in organisations will lead to common principles and clear ownership over information. Additionally, appropriate alignment between corporate governance and BI governance can yield more benefits. This paper provides an insight into the importance and value of BI tools. Key functionalities of BI tools have also been highlighted. Different challenges in gaining true value from BI tools have been examined. Four phases of developing a BI governance framework have been illustrated. The alignment between BI governance and corporate governance has also been explored with a recommended model. Exploratory analysis of two organisations (Premier Healthcare Alliance & BellSouth Telecommunications) to identify how they have utilised BI tools and adopted BI governance has been briefly carried out. The paper posits that if the steps for developing a BI framework are adopted by organisations and the BI framework is aligned with the corporate framework, BI deployment and usage will be successful with reduced risk levels.

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20

Hawking, Paul y Carmine Sellitto. "Business Intelligence Strategy". International Journal of Enterprise Information Systems 11, n.º 1 (enero de 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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21

Bimonte, Sandro, Michel Schneider y Omar Boussaid. "Business Intelligence Indicators". International Journal of Data Warehousing and Mining 12, n.º 4 (octubre de 2016): 75–98. http://dx.doi.org/10.4018/ijdwm.2016100104.

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Nowadays, more and more data are available for decisional analysis and decision-making based on different indicators. Although different decision-making technologies have been developed, the authors note the lack of a conceptual framework for the definition and implementation of these indicators. In this paper, they propose a first classification of these indicators. Furthermore, motivated by the need for formalism for the definition of these indicators at a conceptual level, they present the Business Intelligence Indicators (BI2) UML profile to represent indicators for OLAP, OLTP and streaming technologies. They also present their implementation in existing industrial tools. In addition, they show how these indicators can coexist in the same environment to exchange data through a chaining model and its implementation.

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22

Cravens, David W., William L. Sammon, Mark A. Kurland y Robert Spitalnic. "Business Competitor Intelligence". Journal of Marketing 50, n.º 1 (enero de 1986): 121. http://dx.doi.org/10.2307/1251284.

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23

Miller, Dorothy. "Improving Business Intelligence". International Journal of Business Intelligence Research 1, n.º 4 (octubre de 2010): 47–62. http://dx.doi.org/10.4018/jbir.2010100103.

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Business Intelligence has never been examined with the same rigor as demanded for any other organization investments. Although global investment in Business Intelligence has reached over 6 billion dollars, business managers continue to follow tradition and leave the management of business intelligence to the technocrats. In this paper, the author proposes that a critical need exists to apply the same six sigma methods, which have worked for the rest of the organization to business intelligence operations and products. This proven structured approach, including the associated rigor and metrics, can be customized and integrated into a program which will allow effective management of business intelligence. The proposed Six Sigma program for business intelligence will ensure that an organization can gain control, improve understanding of operations and products, and improve the value of this crucial organization investment.

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24

Mendoza, Rubén A. "Business Intelligence 2.0". International Journal of Business Intelligence Research 1, n.º 4 (octubre de 2010): 63–76. http://dx.doi.org/10.4018/jbir.2010100104.

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Business Intelligence 2.0 is an umbrella term used to refer to a collection of tools that help organizations extend their BI capabilities using Internet platforms. BI 2.0 tools can enable the automatic discovery of distributed software services and data stores, greatly increasing the range of market options for an organization. The development cycle for these tools is still in its early stage, and much work remains. However, some technologies and standards are already well understood in order to make a significant impact. This paper provides an overview of the eXtensible Markup Language (XML) and related technologies supporting the deployment of web services and service-oriented architectures (SOA). The author summarizes the critical importance of these technologies to the emergence of BI 2.0 tools. This paper also explores the current state of Internet-enabled BI activities and strategic considerations for firms considering BI 2.0 options.

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25

Ask, Urban. "Business Intelligence Practices". International Journal of Business Intelligence Research 4, n.º 2 (abril de 2013): 1–18. http://dx.doi.org/10.4018/jbir.2013040101.

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There is considerate interest in Business Intelligence (BI) from many perspectives, but little research describing design and use of BI in real companies is available (Granlund, 2011; Jourdan, Rainer & Marshall, 2008). The aim of this article is to add empirical evidence to the knowledge of BI practices, addressing calls for research. BI practices are reported from 193 large Nordic organizations with the aim to give a broad perspective. Nordic organizations are seen as early movers in the adoption of technology (Beise, 2004) and receptive to adopt innovations (Waarts & Van Everdingen, 2005). However, the picture this paper arrives at is that Nordic organizations design and use of BI solutions is fairly traditional, with a major focus on reporting and analysis that contain financial information. There are signs of “beyond traditional use” of BI, but more field based research is needed to better understand BI in practice.

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Brodzinski, James, Elaine Crable, Thilini Ariyachandra y Mark Frolick. "Mobile Business Intelligence". International Journal of Business Intelligence Research 4, n.º 2 (abril de 2013): 54–66. http://dx.doi.org/10.4018/jbir.2013040104.

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Demand for business intelligence (BI) applications continues to grow at a rapid pace. Business intelligence via mobile devices is the latest frontier to drive demand among organizations interested in BI applications. However, mobile BI is still in its infancy. There are many opportunities to advance the way users use and interact with BI applications using mobile BI. Nevertheless, there are many challenges and issues that still require attention to attain mobile BI success. This paper highlights the state of mobile BI solutions and strategies to consider during a mobile BI implementation. It also discusses the challenges and opportunities mobile BI presents to organizations.

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Tofan, Dragoş Ovidiu. "Business Intelligence Security". Review of Economic and Business Studies 9, n.º 1 (1 de junio de 2016): 157–69. http://dx.doi.org/10.1515/rebs-2016-0030.

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AbstractExcess information characteristic to the current environment leads to the need for a change of the organizations’ perspective and strategy not only through the raw data processing, but also in terms of existing applications generating new information. The overwhelming evolution of digital technologies and web changes led to the adoption of new and adapted internal policies and the emergence of regulations at level of governments or different social organisms. Information security risks arising from the current dynamics demand fast solutions linked to hardware, software and also to education of human resources. Business Intelligence (BI) solutions have their specific evolution in order to bring their contribution to ensure the protection of data through specific components (Big Data, cloud, analytics). The current trend of development of BI applications on mobile devices brings with it a number of shortcomings related to information security and require additional protective measure regarding flows, specific processing and data storage.

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28

Grigori, Daniela, Fabio Casati, Malu Castellanos, Umeshwar Dayal, Mehmet Sayal y Ming-Chien Shan. "Business Process Intelligence". Computers in Industry 53, n.º 3 (abril de 2004): 321–43. http://dx.doi.org/10.1016/j.compind.2003.10.007.

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Pal, Sujoy y Rajanish Dass. "Pervasive Business Intelligence". International Journal of Advanced Pervasive and Ubiquitous Computing 2, n.º 4 (2010): 63–77. http://dx.doi.org/10.4018/ijapuc.2010100104.

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McBride, Neil. "Virtuous Business Intelligence". International Journal of Business Intelligence Research 6, n.º 2 (julio de 2015): 1–17. http://dx.doi.org/10.4018/ijbir.2015070101.

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This paper examines three approaches to ethics and focuses on the development of character and the practice of virtue in business intelligence (BI). The paper describes BI as a tool for mediating the relationships between pairs of stakeholders such as management and customer. Three aspects of the relationship which benefit ethically from the practice of virtues are discussed: the purpose of the BI, the prejudices behind the BI and the power of the stakeholders. The connection between the ethics of BI and the corporate ethics is discussed. Without the practice of virtues, BI may be recruited to support corporate vices of exploitation, exposure, exclusion, coercion, control and concealment. The paper seeks to highlight the importance of ethical issues in BI practice and suggests the development of an ethical balanced scorecard as a vehicle for developing ethical senstitivity.

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31

Hawking, Paul y Carmine Sellitto. "Business Intelligence Strategy". International Journal of Business Intelligence Research 8, n.º 2 (julio de 2017): 17–30. http://dx.doi.org/10.4018/ijbir.2017070102.

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Business Intelligence has been adopted across numerous industry sectors where the commensurate benefits have been reported as being significant to those that fall short of expectations. Indeed, an effective strategy that aligns company objectives and Business Intelligence has been shown to be an important factor in firm realizing organizational benefits. Using a case study approach, the paper documents the key aspects of two companies' Business Intelligence strategy that directly enhanced informational requirements. The paper presents a novel description of Business Intelligence strategies that will provide valuable lessons for not only researchers, but also industry practitioners.

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Kemper, Hans-Georg. "Business Intelligence – BI". Controlling 14, n.º 11 (2002): 665–66. http://dx.doi.org/10.15358/0935-0381-2002-11-665.

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Cochran, Henry T. "Strategic business intelligence". Competitive Intelligence Review 2, n.º 1 (1991): 20–21. http://dx.doi.org/10.1002/cir.3880020111.

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Somi, Subash. "Business intelligence efficiency". International Journal of Engineering in Computer Science 1, n.º 1 (1 de enero de 2019): 36–40. http://dx.doi.org/10.33545/26633582.2019.v1.i1a.9.

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Al-khateeb, Bilal Ahmad Ali. "Business Intelligence (BI)". International Journal of Asian Business and Information Management 15, n.º 1 (12 de marzo de 2024): 1–15. http://dx.doi.org/10.4018/ijabim.340387.

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Generally, BI plays a very significant role in promoting the success of any organization, particularly the universities; however, not all BI projects have been implemented successfully by the universities across the word, suggesting that only a few universities appear to have faith in BI as strategy for success and sustainability particularly in this era where data speak. As a result, this study attempts to establish the relationship between BI and university sustainability and success. Therefore, the major objective of the study is to find an empirical link between BI and university sustainability and success with particular interest in Saudi Arabia. Overall, the study found that business intelligence affects the university sustainability but not its success. It shows that BI assists the university in making good decisions that may sustain the university while ensuring that the university does not fall below break-even in terms of success. By implication, the university can use business intelligence as a strategy for sustainability but not work well for achieving the desired success.

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Hawking, Paul. "Business Intelligence Excellence: A Company’s Journey to Business Intelligence Maturity". International Journal of Technology, Knowledge, and Society 8, n.º 2 (2012): 91–100. http://dx.doi.org/10.18848/1832-3669/cgp/v08i02/56274.

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Ranjan, Jayanthi. "Traditional Business Intelligence vis-a-vis real-time Business Intelligence". International Journal of Information and Communication Technology 1, n.º 3/4 (2008): 298. http://dx.doi.org/10.1504/ijict.2008.024004.

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Rios-Campos, Carlos, Sandra Marcela Zapata Vega, Mariuxi Ileana Tejada-Castro, Erick Orlando Guerrero Zambrano, Dany Jamnier German Barreto Perez, Edilbrando Vega Calderón, Luz Magaly Fernandez Rojas y Irene Marely Ballena Alcantara. "Artificial Intelligence and Business". South Florida Journal of Development 4, n.º 9 (29 de noviembre de 2023): 3547–64. http://dx.doi.org/10.46932/sfjdv4n9-015.

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The general objective of the research was to determine the advances related to the artificial intelligence and business. The specific objectives of the research are to identify the software of AI used in business and the countries that invest more in AI. Methodology, in this research, 62 documents have been selected, carried out in the period 2018 - 2023; including: scientific articles, review articles and information from websites of recognized organizations. Results, every day new AI tools appear that support activities in today's businesses. Conclusions, about the general objective of the research, the importance of AI in business is beginning to be understood. Therefore, it is adopted in various organizational processes worldwide. AI is impacting various human activities, so it is necessary to keep an eye on its evolution. During the pandemic, businesses worldwide had to intensively use information and communication technologies in order to reach their customers. Subsequently, AI is presented as a tool that can radically change business. About the specific objectives of the research, the software of AI used in business are: Salesforce, HubSpot, IBM Watson, ChatGPT, Alteryx Analytics Automation Platform, Amazon SageMaker, GPT-3 model, Adobe Sensei, Marketo, Supply-chain management solutions based on artificial intelligence (AI), Kasisto, Workday, HireVue, Tableau, Power BI, Dynamic Yield, Darktrace, Copy.ai, UiPath, Automation Anywhere, Merative, Google Health, Google Translate. The countries that invest the most in AI are the United States, China and the European Union.

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Jordan, John y Clive Ellen. "Business need, data and business intelligence". Journal of Digital Asset Management 5, n.º 1 (febrero de 2009): 10–20. http://dx.doi.org/10.1057/dam.2008.53.

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Viaene, Stijn. "Linking Business Intelligence into Your Business". IT Professional 10, n.º 6 (noviembre de 2008): 28–34. http://dx.doi.org/10.1109/mitp.2008.128.

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Grothe, Martin. "Collaborative Intelligence Verbindet Business Intelligence und Wissensmanagement". Controlling und Management 47, n.º 2 (abril de 2003): 102–6. http://dx.doi.org/10.1007/bf03254161.

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Jamal Ali, Bayad y Govand Anwar. "Measuring competitive intelligence Network and its role on Business Performance". Vol-6, Issue-2, March - April 2021 6, n.º 2 (2021): 329–45. http://dx.doi.org/10.22161/ijels.62.50.

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Changes and uncertainties have compelled a dramatic change in organizational fundamentals over the last two decades. Owing to internal and external pressures, businesses have been forced to closely track their environments in order to build awareness of opportunities and obstacles in order to stay competitive. The aim of this study is to look into the role of competitive intelligence in small and medium businesses in Iraq's Kurdistan region making business performance. However, the researchers measured the direct impact on business performance at small and medium businesses using five competitive intelligence dimensions (extensiveness' network, third-party strategy, Homophily, Issue awareness, and promotion effort). Furthermore, the researchers used competitive intelligence as a mediator to quantify its impact on business performance, allowing the analysis to explore the indirect role of competitive intelligence. To investigate the role of competitive intelligence in making business performance at small and medium businesses in Iraq's Kurdistan region, the researchers used hierarchal multiple regression and the Sobel test. However, the researchers measured the direct impact on business performance at small and medium businesses using five competitive intelligence dimensions (extensiveness network, third-party strategy, homophily, issue awareness, and promotion effort). Furthermore, the researchers used competitive intelligence as a mediator to quantify its impact on business performance, allowing the analysis to explore the indirect role of competitive intelligence. Competitive intelligence dimensions (extensiveness network, third-party strategy, homophily, issue awareness, and promotion effort) were used to assess the direct and indirect effect of competitive intelligence on business performance at small and medium businesses.

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Chen, Wei-Yu, Shing-Han Li, Mann-Jung Hsiao, Chung-Chiang Hu y Kuo-Ching Tu. "Network Security Analysis by Using Business Intelligence". International Journal of Machine Learning and Computing 5, n.º 6 (diciembre de 2015): 431–38. http://dx.doi.org/10.18178/ijmlc.2015.5.6.547.

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44

Schwerin, Robert y Christoph Kennerknecht. "Business Intelligence und Partizipation". Sozialwirtschaft 30, n.º 2 (2020): 36–37. http://dx.doi.org/10.5771/1613-0707-2020-2-36.

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Im Kreis Pinneberg, wie in vielen anderen Kommunen, werden etwa drei von vier Euro der Haushaltsbudgets für den Sozialbereich aufgewendet. Zusammen mit den politischen Gremien hat man sich daher die Aufgabe gestellt, mit dem Modell einer Integrierten Sozialplanung die Entwicklungen in diesem Segment aktiv zu steuern. Robert Schwerin und Christoph Kennerknecht beschreiben, wie Mit Big Data zusammen mit Bürger- und Trägerbeteilugung dabei helfen kann.

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Jagals, Marvin, Erik Karger y und Marco Boehle. "Self-Service Business Intelligence". Controlling 33, n.º 6 (2021): 50–56. http://dx.doi.org/10.15358/0935-0381-2021-6-50.

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Self-Service BI gestattet Fachbereichen innerhalb einer Organisation in Eigenverantwortung Analysen zu erstellen. In der Praxis existieren dazu jedoch besonders auf Managementebene diverse Herausforderungen. Im Rahmen dieses Beitrags werden Gestaltungsempfehlungen erörtert, die der Managementpraxis zu einer erfolgreichen Implementierung verhelfen.

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Foley, Éric y Manon G. Guillemette. "What is Business Intelligence?" International Journal of Business Intelligence Research 1, n.º 4 (octubre de 2010): 1–28. http://dx.doi.org/10.4018/jbir.2010100101.

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There has been growing corporate interest in business intelligence (BI) as a path to reduced costs, improved service quality, and better decision-making processes. However, while BI has existed for years, it has difficulties reaching what specialists in the field consider its full potential. In this paper, the authors examine disparities in how the constructs of business intelligence are defined and understood, which may impede an understanding of what BI represents to business leaders and researchers. The main objective of this study is to clearly understand this emerging concept of BI. In this regard, the authors analyze articles from the scientific and professional literature to have a comprehensive understanding of business intelligence as both a product and a process. This research proposes a global overview of the conceptual foundations of BI, which can help companies understand their BI initiative and leverage them to the strategic level.

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Dymarsky, Irina. "Champion for Business Intelligence". International Journal of Business Intelligence Research 2, n.º 2 (abril de 2011): 22–36. http://dx.doi.org/10.4018/jbir.2011040102.

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Although Gartner’s EXP 2006 CIO Survey ranked Business Intelligence (BI) as the top technology priority, BI projects face tough competition from other projects in IT portfolios promising more tangible financial returns (Wu & Weitzman, 2006) Two major hurdles that prevent BI projects from shining in portfolios are vague requirements and weak benefits calculations. Both can be addressed by examining and learning from a number of case studies that prove tangible ROI on BI solutions when scoped and designed with a focus on specific, measurable, achievable, results-oriented, and time bound SMART business goals. In order for BI projects to compete in IT portfolios based on financial measures, like ROI, BI champions need to approach BI requirements gathering with the goal of addressing a specific business problem as well as employ standard ways of calculating BI benefits post project go live. By examining common failures with BI requirements and case studies which demonstrate how successful BI implementations translate into tangible benefits for the organization, BI champions develop a toolkit of tips, tricks, and lessons learned for successful requirements gathering, design, implementation, and measure of business results on BI initiatives.

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Glancy, Fletcher H. y Surya B. Yadav. "Business Intelligence Conceptual Model". International Journal of Business Intelligence Research 2, n.º 2 (abril de 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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O’Neill, Daniel. "Business Intelligence Competency Centers". International Journal of Business Intelligence Research 2, n.º 3 (julio de 2011): 21–35. http://dx.doi.org/10.4018/jbir.2011070102.

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Enterprises today continue to invest in business intelligence (BI) initiatives with the hope of providing a strategic advantage to their organizations. Many of these initiatives are supporting the tactical goals of individual business units and not the strategic goals of the enterprise. Although this decentralized approach provides short term gains, it creates an environment where information silos develop and the enterprise as a whole struggles to develop a single version of the truth when it comes to providing strategic information. Enterprises are turning toward a centralized approach to BI which aligns with their overall strategic goals. At the core of the centralized approach is the business intelligence competency center (BICC). This paper details why the centralized BICC approach should be considered an essential component of all enterprise BI initiatives. Examining case studies of BICC implementations details the benefits realized by real world companies who have taken this approach. It is also important to provide analysis of the two BI approaches in the areas of BI process and BI technology/data and people relations. The findings indicate the benefits of the centralized BICC outweigh the deficiencies of the decentralized approach.

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Webb, Leticia R. "Business Intelligence in Audit". International Journal of Business Intelligence Research 3, n.º 3 (julio de 2012): 42–53. http://dx.doi.org/10.4018/jbir.2012070104.

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Since 2002, regulations have changed the landscape of internal audit as well as how many internal audit departments are viewed by senior management and the board, making it difficult for internal audit, especially small and medium departments, to maintain a role in the risk management process. Many companies are beginning to realize the benefit of using business intelligence in the risk management process. By finding ways to get involved in those efforts, internal audit can again provide value and regain a seat at the risk management table.

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