Business intelligence : from conventional to cognitive

Technological systems enhance organizations since 1958 and are the ground basis of a strong managerial operation in today´s business competition. Based on a literature review that identifies past, present and future applications of technology from business intelligence to artificial intelligence. Th...

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Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
spa
OAI Identifier:
oai:repository.urosario.edu.co:10336/19040
Acceso en línea:
https://doi.org/10.48713/10336_19040
http://repository.urosario.edu.co/handle/10336/19040
Palabra clave:
Business intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Conocimiento
Business Intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Inteligencia artificial
Internet de las cosas
Aprendizaje automático (Inteligencia artificial)
Rights
License
Atribución-NoComercial-SinDerivadas 2.5 Colombia
id EDOCUR2_1f58c7a6122578265746907bf3c6e5a1
oai_identifier_str oai:repository.urosario.edu.co:10336/19040
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
dc.title.spa.fl_str_mv Business intelligence : from conventional to cognitive
title Business intelligence : from conventional to cognitive
spellingShingle Business intelligence : from conventional to cognitive
Business intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Conocimiento
Business Intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Inteligencia artificial
Internet de las cosas
Aprendizaje automático (Inteligencia artificial)
title_short Business intelligence : from conventional to cognitive
title_full Business intelligence : from conventional to cognitive
title_fullStr Business intelligence : from conventional to cognitive
title_full_unstemmed Business intelligence : from conventional to cognitive
title_sort Business intelligence : from conventional to cognitive
dc.contributor.advisor.none.fl_str_mv Gómez Cruz, Nelson Alfonso
dc.subject.spa.fl_str_mv Business intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
topic Business intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Conocimiento
Business Intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
Inteligencia artificial
Internet de las cosas
Aprendizaje automático (Inteligencia artificial)
dc.subject.ddc.spa.fl_str_mv Conocimiento
dc.subject.keyword.spa.fl_str_mv Business Intelligence
Analytics
Cognitive
Internet of things
Machine learning
Artificial intelligence
dc.subject.lemb.spa.fl_str_mv Inteligencia artificial
Internet de las cosas
Aprendizaje automático (Inteligencia artificial)
description Technological systems enhance organizations since 1958 and are the ground basis of a strong managerial operation in today´s business competition. Based on a literature review that identifies past, present and future applications of technology from business intelligence to artificial intelligence. This article offers an understanding of which technological advances are applied in organizations to adapt and survive within an ever-changing environment in business world today. Business intelligence´s definition and key divisions are described to carry on a wide explanation due to its scope. Based in a state-of-the-art literature revision and going through several definitions, BI it is analyzed as a process and as technological aid. From key divisions in its application such as: reporting, analysis, monitoring and prediction to its extensions based on time frames in operational and strategic bids. BI is the starting point to excel why having a decision support making tool is key to hedge the risk from failure to be an outstanding tool to increase profits. How can systems create for themselves prediction modules that optimize and later adapt to future scenarios based on historic data and how its adaptivity is key. Therefore, new technologies are emerging at a neck breaking speed. Hence, this article explains and help to understand their scope and importance within the world we live in and why companies must innovate and cope with them when building their industry to new horizons. Internet of things, machine learning and artificial intelligence are the new emerging and disruptive technologies that are being implemented in all industries creating new trends and challenges to manage.
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2019-02-11T20:41:43Z
dc.date.available.none.fl_str_mv 2019-02-11T20:41:43Z
dc.date.created.none.fl_str_mv 2019-02-07
dc.date.issued.none.fl_str_mv 2019
dc.type.eng.fl_str_mv bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.document.spa.fl_str_mv Artículo
dc.type.spa.spa.fl_str_mv Trabajo de grado
dc.identifier.doi.none.fl_str_mv https://doi.org/10.48713/10336_19040
dc.identifier.uri.none.fl_str_mv http://repository.urosario.edu.co/handle/10336/19040
url https://doi.org/10.48713/10336_19040
http://repository.urosario.edu.co/handle/10336/19040
dc.language.iso.none.fl_str_mv spa
language spa
dc.rights.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 2.5 Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/2.5/co/
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 2.5 Colombia
Abierto (Texto Completo)
http://creativecommons.org/licenses/by-nc-nd/2.5/co/
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad del Rosario
dc.publisher.department.spa.fl_str_mv Facultad de administración
dc.publisher.program.spa.fl_str_mv Administrador de negocios internacionales
institution Universidad del Rosario
dc.source.bibliographicCitation.spa.fl_str_mv Abdelkerim Rezgui, R. B. (2016). Un système d’évaluation de l’impact des décisions pour la Business Intelligence Adaptative. Ingeniere des systems d`information , 21, 103-124.
AI, P. (2018). Obtenido de https://www.partnershiponai.org/about/
Alphaydin, E. (2010). Introduction to machine learning. London: The MIT press.
Anderson, S. L. (2008). Asimov’s ‘‘three laws of robotics’’ and machine. AI & Soc, 477–493.
Apex. (November de 2018). Obtenido de https://www.apex.com/four-main-types-bi/
Atzori, L., Iera, A., & Morabito, G. (14 de May de 2010). The Internet of Things: A survey. Computer Networks, 2787–2805.
Banafa, A. (14 de March de 2017). Three Major Challenges Facing IoT. Obtenido de https://iot.ieee.org/newsletter/march-2017/three-major-challenges-facing-iot.html
Bostrom, N. (2003). Ethical Issues in Advanced Artificial Intelligence. Oxford: Oxford University.
Brown, J., Cuzzocrea, A., Kresta, M., Kristjanson, K., Leung, C., & Tebinka, T. ( 2018). A machine learning tool for supporting advanced knowledge discovery from chess game data. 16th IEEE International Conference on Machine Learning and Applications, (págs. 649-654). Cancun.
Cambridge, D. (18 de November de 2018). https://dictionary.cambridge.org. Obtenido de https://dictionary.cambridge.org/dictionary/english/data
Cambridge. (2018). Obtenido de https://dictionary.cambridge.org/dictionary/english-spanish/artificial
Cambridge. (2018). Obtenido de https://dictionary.cambridge.org/dictionary/english-spanish/intelligence
Campbell, M., Jr, A. H., & Feng-hsiung, b. (2002). Deep Blue. Artificial Intelligence, 134, 57-83. Obtenido de https://doi.org/10.1016/S0004-3702(01)00129-1
Chen, Y., Argentinis, E., & Weber, G. (2016). IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research. Clinical Therapeutics, 38, 688-701. Obtenido de https://doi.org/10.1016/j.clinthera.2015.12.001
Chiang, R. H., Chen, H.-c., & Storey, V. C. (2010). Business Intelligence Research. Minnesota: MIS Quarterly
CNN. (2018 de January de 2016). Why Elon Musk is worried about artificial intelligence. Obtenido de https://www.youtube.com/watch?v=US95slMMQis
Daffodil. (30 de July de 2017). 9 Applications of Machine Learning from Day-to-Day Life. Obtenido de https://medium.com/app-affairs/9-applications-of-machine-learning-from-day-to-day-life-112a47a429d0
DataRobot. (2018). Unsupervised Machine Learning. Obtenido de https://www.datarobot.com/wiki/unsupervised-machine-learning/
Devi, S., & Kalia, D. A. (2015). Study of Data Cleaning & Comparison of Data Cleaning Tools. International Journal of Computer Science and Mobile Computing, 4(3), 360-370.
Devi, S., & Kalia, D. A. (2015). Study of Data Cleaning & Comparison of Data Cleaning Tools. International Journal of Computer Science and Mobile Computing, 4(3), 360-370.
Dietrich, D., Heller, B., & Yang, B. (2015). Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. Indianapolis, United States of America: John Wiley & Sons, Inc.
Enciclopedia. (2018). Artificial Intelligence. Obtenido de https://www.encyclopedia.com/science-and-technology/computers-and-electrical-engineering/computers-and-computing/artificial-intelligence
Erb, B. (2016). Artificial Intelligence & Theory of Mind.
Gandhi, N., & Armstrong, L. J. (2016). A review of the application of data mining techniques for decision making in agriculture. (IEEE, Ed.) 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), 2.
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Gartner. (2018). IT Glossary. Obtenido de https://www.gartner.com/it-glossary/big-data/
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Geotab. (25 de May de 2018). 6 Steps for Data Cleaning and Why it Matters. Obtenido de https://www.geotab.com/blog/data-cleaning/
Giorgio, P., Marzin, K., Lee, S., & Vonderhaar, M. (2018). Internet of Things (IoT): Bringing IoT to Sports Analytics, Player Safety, and Fan. Deloitte Development LLC.
GN, C. K. (31 de August de 2018). Artificial Intelligence: Definition, Types, Examples, Technologies. Obtenido de https://medium.com/@chethankumargn/artificial-intelligence-definition-types-examples-technologies-962ea75c7b9b
Golfarelli, M., Rizzi, S., & Cella, I. (2004). Beyond Data Warehousing: What’s Next in Business Intelligence? . Proceedings of the 7th ACM international, 1.
Gorbea, P. S., & Madera, J. M. (Agosto de 2017). Diseño de un data warehouse para medir el desarrollo disciplinar en instituciones académicas. INVESTIGACIÓN BIBLIOTECOLÓGICA, 31(72), 161-181. Obtenido de http://rev-ib.unam.mx/ib/index.php/ib/article/view/57828
H.Witten, I., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques. San Francisco: Morgan Kaufman Publishers.
Hassan, M., El Desouky, A., Elghamrawy, S., & Sarhan, A. (2019). A Hybrid Real-time remote monitoring framework with NB-WOA algorithm for patients with chronic diseases. Future Generation Computer Systems, 77-95.
Hazen, B. T., Boone, C. A., Ezell, J. D., & AllisonJones-Farmer, L. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72-80.
Heltzel, P. (12 de February de 2018). www.cio.com. Obtenido de https://www.cio.com/article/3254744/emerging-technology/technologies-that-will-disrupt-business.html
Hintzed, A. (14 de November de 2016). Understanding the Four Types of Artificial Intelligence. Obtenido de http://www.govtech.com/computing/Understanding-the-Four-Types-of-Artificial-Intelligence.html
Hitachi. (26 de Junio de 2014). What is Business Intelligence (BI). Toronto, Canada. Obtenido de https://www.youtube.com/watch?v=hDJdkcdG1iA
Hougland, B. (17 de December de 2014). www.tedx.com. Obtenido de https://www.youtube.com/watch?v=_AlcRoqS65E
HUGH J. WATSON, B. H.-L. (December de 2009). REAL-TIME BUSINESS INTELLIGENCE: BEST PRACTICES AT CONTINENTAL AIRLINES. EDPACS: The EDP Audit, Control, and Security, 2-17.
IBM. (2018). Shifting toward Enterprise-grade AI: Resolving data and skills gaps to realize value. Armonk, NY: IBM Institute for Business Value.
IBM. (3 de September de 2015). How It Works: Internet of Things. Obtenido de https://www.youtube.com/watch?v=QSIPNhOiMoE
Jones, M., Sidorova, A., & Isk, O. (23 de December de 2012). Business intelligence success: The roles of BI capabilities and decision enviroments. 13-14.
Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, and prospects. American Association for the Advancement of Science, 249(6245).
Kato, S., Ando, M., Kondo, T., Yoshida, Y., Honda, H., & Maruyama, S. (May de 2018). Lifestyle intervention using Internet of Things (IoT) for the elderly: A study protocol for a randomized control trial (the BEST-LIFE study). Nagoya Journal of Med Sci., 175-182.
Kopetz, H. (2011). Real-Time Systems: Design Principles for Distributed Embedded Applications. Boston: Springer.
Kuhn, M., & Jhonson, K. (2016). Applied Predictive Modeling (Vol. 5). New York: Springer.
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Luhn, H. P. (1958). A Business Intelligence System . IMB Journal .
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Marr, B. (23 de March de 2016). What Everyone Should Know About Cognitive Computing. Obtenido de https://www.forbes.com/sites/bernardmarr/2016/03/23/what-everyone-should-know-about-cognitive-computing/#332913b55088
Michalewicz, Z., Schmidt, M., Michalewicz, M., & Constantine, C. (2010). Adaptive Business Inteligence. Berlin - Heidelberg: Springer.
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Pirttimäki, V. (2 de June de 2007). Conceptual analysis of business intelligence. South African Journal Of Information and Management, 9, 2-5.
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Rahm, E., & Do, H. H. (2015). Data Cleaning: Problems and Current Approaches. University of Leipzig.
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Stefan Debortoli, M., Müller, D. O., & Brocke, P. D. (2014). Comparing Business Intelligence and Big Data Skills. 5.
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Triana, J. A., Hernández, C. A., Martínez, A. B., Lista, E. A., & Flórez, L. C. (2013). Business intelligence solution for managing educational resources and physical. AVANCES Investigación en Ingeniería, 10(1), 11.
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Viktor Mayer-Schönberger, K. C. (2014). Book Review. En K. C. Viktor Mayer-Schönberger-, Big Data: A Revolution That Will Transform How We Live, Work, and Think (Vol. 179, págs. 1143-1144). Oxford: American Journal of Epidemiology.
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spelling Gómez Cruz, Nelson Alfonso7319118600Ramírez Linares, Andrés FelipeAdministrador de Negocios InternacionalesFull time546292c7-c875-4288-90c5-be73cb4ab9f46002019-02-11T20:41:43Z2019-02-11T20:41:43Z2019-02-072019Technological systems enhance organizations since 1958 and are the ground basis of a strong managerial operation in today´s business competition. Based on a literature review that identifies past, present and future applications of technology from business intelligence to artificial intelligence. This article offers an understanding of which technological advances are applied in organizations to adapt and survive within an ever-changing environment in business world today. Business intelligence´s definition and key divisions are described to carry on a wide explanation due to its scope. Based in a state-of-the-art literature revision and going through several definitions, BI it is analyzed as a process and as technological aid. From key divisions in its application such as: reporting, analysis, monitoring and prediction to its extensions based on time frames in operational and strategic bids. BI is the starting point to excel why having a decision support making tool is key to hedge the risk from failure to be an outstanding tool to increase profits. How can systems create for themselves prediction modules that optimize and later adapt to future scenarios based on historic data and how its adaptivity is key. Therefore, new technologies are emerging at a neck breaking speed. Hence, this article explains and help to understand their scope and importance within the world we live in and why companies must innovate and cope with them when building their industry to new horizons. Internet of things, machine learning and artificial intelligence are the new emerging and disruptive technologies that are being implemented in all industries creating new trends and challenges to manage.application/pdfhttps://doi.org/10.48713/10336_19040 http://repository.urosario.edu.co/handle/10336/19040spaUniversidad del RosarioFacultad de administraciónAdministrador de negocios internacionalesAtribución-NoComercial-SinDerivadas 2.5 ColombiaAbierto (Texto Completo)EL AUTOR, manifiesta que la obra objeto de la presente autorización es original y la realizó sin violar o usurpar derechos de autor de terceros, por lo tanto la obra es de exclusiva autoría y tiene la titularidad sobre la misma. PARGRAFO: En caso de presentarse cualquier reclamación o acción por parte de un tercero en cuanto a los derechos de autor sobre la obra en cuestión, EL AUTOR, asumirá toda la responsabilidad, y saldrá en defensa de los derechos aquí autorizados; para todos los efectos la universidad actúa como un tercero de buena fe. EL AUTOR, autoriza a LA UNIVERSIDAD DEL ROSARIO, para que en los términos establecidos en la Ley 23 de 1982, Ley 44 de 1993, Decisión andina 351 de 1993, Decreto 460 de 1995 y demás normas generales sobre la materia, utilice y use la obra objeto de la presente autorización. -------------------------------------- POLITICA DE TRATAMIENTO DE DATOS PERSONALES. Declaro que autorizo previa y de forma informada el tratamiento de mis datos personales por parte de LA UNIVERSIDAD DEL ROSARIO para fines académicos y en aplicación de convenios con terceros o servicios conexos con actividades propias de la academia, con estricto cumplimiento de los principios de ley. Para el correcto ejercicio de mi derecho de habeas data cuento con la cuenta de correo habeasdata@urosario.edu.co, donde previa identificación podré solicitar la consulta, corrección y supresión de mis datos.http://creativecommons.org/licenses/by-nc-nd/2.5/co/http://purl.org/coar/access_right/c_abf2Abdelkerim Rezgui, R. B. (2016). Un système d’évaluation de l’impact des décisions pour la Business Intelligence Adaptative. Ingeniere des systems d`information , 21, 103-124.AI, P. (2018). Obtenido de https://www.partnershiponai.org/about/Alphaydin, E. (2010). Introduction to machine learning. London: The MIT press.Anderson, S. L. (2008). Asimov’s ‘‘three laws of robotics’’ and machine. AI & Soc, 477–493.Apex. (November de 2018). Obtenido de https://www.apex.com/four-main-types-bi/Atzori, L., Iera, A., & Morabito, G. (14 de May de 2010). The Internet of Things: A survey. Computer Networks, 2787–2805.Banafa, A. (14 de March de 2017). Three Major Challenges Facing IoT. Obtenido de https://iot.ieee.org/newsletter/march-2017/three-major-challenges-facing-iot.htmlBostrom, N. (2003). Ethical Issues in Advanced Artificial Intelligence. Oxford: Oxford University.Brown, J., Cuzzocrea, A., Kresta, M., Kristjanson, K., Leung, C., & Tebinka, T. ( 2018). A machine learning tool for supporting advanced knowledge discovery from chess game data. 16th IEEE International Conference on Machine Learning and Applications, (págs. 649-654). Cancun.Cambridge, D. (18 de November de 2018). https://dictionary.cambridge.org. Obtenido de https://dictionary.cambridge.org/dictionary/english/dataCambridge. (2018). Obtenido de https://dictionary.cambridge.org/dictionary/english-spanish/artificialCambridge. (2018). Obtenido de https://dictionary.cambridge.org/dictionary/english-spanish/intelligenceCampbell, M., Jr, A. H., & Feng-hsiung, b. (2002). Deep Blue. Artificial Intelligence, 134, 57-83. Obtenido de https://doi.org/10.1016/S0004-3702(01)00129-1Chen, Y., Argentinis, E., & Weber, G. (2016). IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research. Clinical Therapeutics, 38, 688-701. Obtenido de https://doi.org/10.1016/j.clinthera.2015.12.001Chiang, R. H., Chen, H.-c., & Storey, V. C. (2010). Business Intelligence Research. Minnesota: MIS QuarterlyCNN. (2018 de January de 2016). Why Elon Musk is worried about artificial intelligence. Obtenido de https://www.youtube.com/watch?v=US95slMMQisDaffodil. (30 de July de 2017). 9 Applications of Machine Learning from Day-to-Day Life. Obtenido de https://medium.com/app-affairs/9-applications-of-machine-learning-from-day-to-day-life-112a47a429d0DataRobot. (2018). Unsupervised Machine Learning. Obtenido de https://www.datarobot.com/wiki/unsupervised-machine-learning/Devi, S., & Kalia, D. A. (2015). Study of Data Cleaning & Comparison of Data Cleaning Tools. International Journal of Computer Science and Mobile Computing, 4(3), 360-370.Devi, S., & Kalia, D. A. (2015). Study of Data Cleaning & Comparison of Data Cleaning Tools. International Journal of Computer Science and Mobile Computing, 4(3), 360-370.Dietrich, D., Heller, B., & Yang, B. (2015). Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. Indianapolis, United States of America: John Wiley & Sons, Inc.Enciclopedia. (2018). Artificial Intelligence. Obtenido de https://www.encyclopedia.com/science-and-technology/computers-and-electrical-engineering/computers-and-computing/artificial-intelligenceErb, B. (2016). Artificial Intelligence & Theory of Mind.Gandhi, N., & Armstrong, L. J. (2016). A review of the application of data mining techniques for decision making in agriculture. (IEEE, Ed.) 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), 2.Gartner. (2 de April de 2012). Obtenido de https://www.gartner.com/newsroom/id/1971516Gartner. (2018). IT Glossary. Obtenido de https://www.gartner.com/it-glossary/big-data/Gartner. (3 de February de 2016). Obtenido de https://www.gartner.com/newsroom/id/3198917Geotab. (25 de May de 2018). 6 Steps for Data Cleaning and Why it Matters. Obtenido de https://www.geotab.com/blog/data-cleaning/Giorgio, P., Marzin, K., Lee, S., & Vonderhaar, M. (2018). Internet of Things (IoT): Bringing IoT to Sports Analytics, Player Safety, and Fan. Deloitte Development LLC.GN, C. K. (31 de August de 2018). Artificial Intelligence: Definition, Types, Examples, Technologies. Obtenido de https://medium.com/@chethankumargn/artificial-intelligence-definition-types-examples-technologies-962ea75c7b9bGolfarelli, M., Rizzi, S., & Cella, I. (2004). Beyond Data Warehousing: What’s Next in Business Intelligence? . Proceedings of the 7th ACM international, 1.Gorbea, P. S., & Madera, J. M. (Agosto de 2017). Diseño de un data warehouse para medir el desarrollo disciplinar en instituciones académicas. INVESTIGACIÓN BIBLIOTECOLÓGICA, 31(72), 161-181. Obtenido de http://rev-ib.unam.mx/ib/index.php/ib/article/view/57828H.Witten, I., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques. San Francisco: Morgan Kaufman Publishers.Hassan, M., El Desouky, A., Elghamrawy, S., & Sarhan, A. (2019). A Hybrid Real-time remote monitoring framework with NB-WOA algorithm for patients with chronic diseases. Future Generation Computer Systems, 77-95.Hazen, B. T., Boone, C. A., Ezell, J. D., & AllisonJones-Farmer, L. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72-80.Heltzel, P. (12 de February de 2018). www.cio.com. Obtenido de https://www.cio.com/article/3254744/emerging-technology/technologies-that-will-disrupt-business.htmlHintzed, A. (14 de November de 2016). Understanding the Four Types of Artificial Intelligence. Obtenido de http://www.govtech.com/computing/Understanding-the-Four-Types-of-Artificial-Intelligence.htmlHitachi. (26 de Junio de 2014). What is Business Intelligence (BI). Toronto, Canada. Obtenido de https://www.youtube.com/watch?v=hDJdkcdG1iAHougland, B. (17 de December de 2014). www.tedx.com. Obtenido de https://www.youtube.com/watch?v=_AlcRoqS65EHUGH J. WATSON, B. H.-L. (December de 2009). REAL-TIME BUSINESS INTELLIGENCE: BEST PRACTICES AT CONTINENTAL AIRLINES. EDPACS: The EDP Audit, Control, and Security, 2-17.IBM. (2018). Shifting toward Enterprise-grade AI: Resolving data and skills gaps to realize value. Armonk, NY: IBM Institute for Business Value.IBM. (3 de September de 2015). How It Works: Internet of Things. Obtenido de https://www.youtube.com/watch?v=QSIPNhOiMoEJones, M., Sidorova, A., & Isk, O. (23 de December de 2012). Business intelligence success: The roles of BI capabilities and decision enviroments. 13-14.Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, and prospects. American Association for the Advancement of Science, 249(6245).Kato, S., Ando, M., Kondo, T., Yoshida, Y., Honda, H., & Maruyama, S. (May de 2018). Lifestyle intervention using Internet of Things (IoT) for the elderly: A study protocol for a randomized control trial (the BEST-LIFE study). Nagoya Journal of Med Sci., 175-182.Kopetz, H. (2011). Real-Time Systems: Design Principles for Distributed Embedded Applications. Boston: Springer.Kuhn, M., & Jhonson, K. (2016). Applied Predictive Modeling (Vol. 5). New York: Springer.Lahrmann, G., Marx, F., Winter, R., & Wortmann, F. (2011). Business Intelligence Maturity: Development and Evaluation of a Theoretical Model. (U. o. Gallen, Ed.) 44, 2.Luhn, H. P. (1958). A Business Intelligence System . IMB Journal .Marr, B. (14 de February de 2018). www.forbes.com. Obtenido de https://www.forbes.com/sites/bernardmarr/2018/02/14/the-key-definitions-of-artificial-intelligence-ai-that-explain-its-importance/#e649af04f5d8Marr, B. (23 de March de 2016). What Everyone Should Know About Cognitive Computing. Obtenido de https://www.forbes.com/sites/bernardmarr/2016/03/23/what-everyone-should-know-about-cognitive-computing/#332913b55088Michalewicz, Z., Schmidt, M., Michalewicz, M., & Constantine, C. (2010). Adaptive Business Inteligence. Berlin - Heidelberg: Springer.Mostafa, H., Thurow, K., Habil, D. I., Stoll, R., & Habil, D. M. (2017). Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices. Healthc Inform Res, 4-15.Nilsson, N. J. (1996). Book review: Stuart Russell and Peter Norvig, Artijcial Intelligence: A Modem Approach. Artificial Intelligence, 369-380.Ning, H., & Wang, Z. (April de 2011). Future Internet of Things Architecture: Like Mankind Neural System or Social Organization Framework? IEEE COMMUNICATIONS LETTERS, 15(4), 2.Oracle. (2018). Oracle Big Data. Obtenido de https://www.oracle.com/big-data/guide/what-is-big-data.htmlPaul, F. (26 de November de 2018). Obtenido de https://www.networkworld.com/article/3322517/internet-of-things/a-critical-look-at-gartners-top-10-iot-trends.htmlPaulaGonzález, M., JesúsLorés, & AntoniGranollers. (2008). Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use. Information and Software Technology, 547-568.Peart, A. (22 de June de 2017). www.artificial-solutions.com. Obtenido de https://www.artificial-solutions.com/blog/homage-to-john-mccarthy-the-father-of-artificial-intelligencePirttimäki, V. (2 de June de 2007). Conceptual analysis of business intelligence. South African Journal Of Information and Management, 9, 2-5.Price, R. (23 de May de 2018). Months after a fatal crash, Uber lays off 300 workers as it pulls its self-driving car tests out of Arizona. Obtenido dePrice, R. (23 de May de 2018). Months after a fatal crash, Uber lays off 300 workers as it pulls its self-driving car tests out of Arizona. Obtenido de 33 https://www.Rahm, E., & Do, H. H. (2015). Data Cleaning: Problems and Current Approaches. University of Leipzig.Raona. (4 de September de 2018). Adiós a nuestros problemas gracias al Cognitive Computing. Obtenido de https://www.raona.com/adios-a-nuestros-problemas-gracias-al-cognitive-computing/Rashed K. Salem, A. S. (14 de March de 2016). Fixing Rules for Data Cleaning based on Conditional. Future Computing and Informatics Journal, 11-15.Richard G. Vedder-, M. T. (1999). Ceo and Cio Perspectives on Competitive Intelligence. Communications of the ACM, 42(8), 108-116.Rubio, J. M., & Crawford, B. (2014). An approach towards the integration of Adaptive Business Intelligent and Constraint Programming . Pontificia universidad catolica del valparaiso, 2.SAP. (2018). Obtenido de https://www.sap.com/latinamerica/products/leonardo.htmlSAP. (26 de April de 2018). Obtenido de https://www.soapeople.com/blog/6-reasons-why-sap-leonardo-is-the-future-of-intelligent-erpShah, J., & Mishra, B. (2016). Customized IoT enabled Wireless Sensing and Monitoring Platform. 3rd International Conference on Innovations in Automation and Mechatronics Engineering, (págs. 256 – 263 ). Gandhinaga: VLSI and Embedded Systems Research Group.Shollo, A., & Kautz, K. (2010). Towards an Understanding of Business Intelligence. Australasian Conference on Information Systems. Brisbane, QeenslandSommer, P. (20 de November de 2017). Obtenido de https://www.ibm.com/blogs/nordic-msp/artificial-intelligence-machine-learning-cognitive-computing/Soni, D. (22 de March de 2018). Supervised vs. Unsupervised Learning: Understanding the differences between the two main types of machine learning methods. Obtenido de https://towardsdatascience.com/supervised-vs-unsupervised-learning-14f68e32ea8dSparks, O. (11 de Enero de 2017). www.Youtube.com. Obtenido de https://www.youtube.com/watch?v=f_uwKZIAeM0Stefan Debortoli, M., Müller, D. O., & Brocke, P. D. (2014). Comparing Business Intelligence and Big Data Skills. 5.Su, X. (2018). Introduction to Big Data. Learning material is developed for course IINI3012 Big Data, 2.Surajit Chaudhuri, U. D. (Agosto de 2011). An Overview of business Intelligence Technology. Communications of the acm, 54(8), 88-98.Techopedia. (2018). Obtenido de https://www.techopedia.com/definition/13832/operational-business-intelligence-obiTechopedia. (30 de October de 2018). Obtenido de https://www.techopedia.com/definition/344/business-analytics-baTechopedia. (December de 2018). www.techopedia.com/. Obtenido de https://www.techopedia.com/definition/3739/algorithmTegmark, M. (2018). 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Oxford: American Journal of Epidemiology.Weldon, D. (12 de June de 2018). Obtenido de https://www.information-management.com/slideshow/10-predictions-on-advanced-analytics-and-business-intelligence-trendsWixom, B., & Watson, H. (2010). The BI-Based Organization. International Journal of Business Intelligence Research, 14.Wong, M.-H. C.-L. (4 de May de 2011). A review of business intelligence and its maturity models. African Journal of Business Management, 5, 3424-3428. Obtenido de http://www.academicjournals.org/AJBMYang, S.-H. (2014). Internet of Things. In: Wireless Sensor Networks. Signals and Communication Technology. London: Springer.Zhao, Y., Yu, Y., Li, Y., Han, G., & Du, X. (2018). Machine learning based privacy-preserving fair data trading. 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