Covid-19 y Business Analytics, ¿un caso asintomático?
The importance of data for decision-making has been higher today than at any other time in history. For this reason, companies have decided to use this data together with the tools provided by Business Analytics (BA) to support decision-making processes to generate value in their organizations. Howe...
- Autores:
-
Freire Tarazona, Santiago Efraín
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2021
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/51047
- Acceso en línea:
- http://hdl.handle.net/1992/51047
- Palabra clave:
- Analítica de negocios
Organizaciones
Negocios
COVID-19 (Enfermedad)
Administración
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Covid-19 y Business Analytics, ¿un caso asintomático? |
| title |
Covid-19 y Business Analytics, ¿un caso asintomático? |
| spellingShingle |
Covid-19 y Business Analytics, ¿un caso asintomático? Analítica de negocios Organizaciones Negocios COVID-19 (Enfermedad) Administración |
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Covid-19 y Business Analytics, ¿un caso asintomático? |
| title_full |
Covid-19 y Business Analytics, ¿un caso asintomático? |
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Covid-19 y Business Analytics, ¿un caso asintomático? |
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Covid-19 y Business Analytics, ¿un caso asintomático? |
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Covid-19 y Business Analytics, ¿un caso asintomático? |
| dc.creator.fl_str_mv |
Freire Tarazona, Santiago Efraín |
| dc.contributor.advisor.none.fl_str_mv |
Ferro Cortés, Luz Marína Navarro Forero, Camilo Andrés |
| dc.contributor.author.none.fl_str_mv |
Freire Tarazona, Santiago Efraín |
| dc.contributor.jury.none.fl_str_mv |
Camacho Ahumada, Sonia Marcela |
| dc.subject.armarc.spa.fl_str_mv |
Analítica de negocios Organizaciones Negocios COVID-19 (Enfermedad) |
| topic |
Analítica de negocios Organizaciones Negocios COVID-19 (Enfermedad) Administración |
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Administración |
| description |
The importance of data for decision-making has been higher today than at any other time in history. For this reason, companies have decided to use this data together with the tools provided by Business Analytics (BA) to support decision-making processes to generate value in their organizations. However, the measures taken to combat the COVID-19 pandemic, such as quarantines and social distancing, have radically changed consumer behaviors, this is reflected in the data, which makes it impossible to use some models in the way they were used before the pandemic. Therefore, this document seeks to answer the question of: How has the adaptation process been in the use of Business Analytics (BA), during the pandemic? This is in order to understand, from the case study, the process of adapting Business Analytics in contexts of high uncertainty (COVID-19) in emerging countries and in industries that make intensive use of these tools. In this way, it was concluded that the process has not fundamentally changed, so it could be considered an asymptomatic case, but some additional activities have been included. Specifically, a proposition related to the calibration of the DDDM process is generated and hypotheses are generated about: the speed with which the process is carried out, the new data sources and the necessary new analyzes of the models. In addition, factors were found that have become relevant due to the context of COVID-19, these are the relationship with the real sector of the companies studied and the architecture that supports the DDDM processes. |
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2021 |
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2021-08-10T18:07:05Z |
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2021 |
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http://hdl.handle.net/1992/51047 |
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23798.pdf |
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Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ferro Cortés, Luz Marínavirtual::16326-1Navarro Forero, Camilo Andrésvirtual::16327-1Freire Tarazona, Santiago Efraín4a145472-86a0-4e23-a629-774239474c2b500Camacho Ahumada, Sonia Marcela2021-08-10T18:07:05Z2021-08-10T18:07:05Z2021http://hdl.handle.net/1992/5104723798.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/The importance of data for decision-making has been higher today than at any other time in history. For this reason, companies have decided to use this data together with the tools provided by Business Analytics (BA) to support decision-making processes to generate value in their organizations. However, the measures taken to combat the COVID-19 pandemic, such as quarantines and social distancing, have radically changed consumer behaviors, this is reflected in the data, which makes it impossible to use some models in the way they were used before the pandemic. Therefore, this document seeks to answer the question of: How has the adaptation process been in the use of Business Analytics (BA), during the pandemic? This is in order to understand, from the case study, the process of adapting Business Analytics in contexts of high uncertainty (COVID-19) in emerging countries and in industries that make intensive use of these tools. In this way, it was concluded that the process has not fundamentally changed, so it could be considered an asymptomatic case, but some additional activities have been included. Specifically, a proposition related to the calibration of the DDDM process is generated and hypotheses are generated about: the speed with which the process is carried out, the new data sources and the necessary new analyzes of the models. In addition, factors were found that have become relevant due to the context of COVID-19, these are the relationship with the real sector of the companies studied and the architecture that supports the DDDM processes.La importancia de los datos para la toma de decisiones ha sido más alta en la actualidad que en cualquier otro momento de la historia. Por tal motivo, las empresas han decidido utilizar las herramientas que brinda el Business Analytics (BA) para apoyar los procesos de toma de decisiones (DDDM), con el fin de generar valor en sus organizaciones. Sin embargo, las medidas tomadas para combatir la pandemia del COVID-19, como las cuarentenas y el distanciamiento social, han cambiado radicalmente los comportamientos de los consumidores. Esto se ve reflejado en los datos, lo cual imposibilita el uso de algunos modelos de la forma en la que usaban antes de la pandemia. Por tanto, con este documento se busca responder la pregunta de: ¿Cómo ha sido el proceso de adaptación en el uso de las herramientas del Business Analytics (BA) en tiempos de pandemia? Esto con el fin de comprender, a partir del estudio de casos, el proceso de adaptación de Business Analytics en contextos de alta incertidumbre, (COVID-19) en países emergentes y en industrias que haga uso intensivo de estas herramientas. De esta forma, se llegó a la conclusión que el proceso no ha cambiado en lo fundamental, por lo que se podría considerar un caso asintomático, pero sí se han incluido algunas actividades adicionales. En específico se genera una proposición relacionada con la calibración del proceso DDDM y se generan hipótesis sobre: la rapidez con la que se lleva a cabo el proceso, las nuevas fuentes de datos y los nuevos análisis necesarios de los modelos. Además, se encontraron factores que han cobrado relevancia debido al contexto del COVID-19, estos son la relación con el sector real de las empresas estudiadas y la arquitectura que soporta los procesos de DDDM.AdministradorPregrado56 hojasapplication/pdfspaUniversidad de los AndesAdministraciónFacultad de AdministraciónCovid-19 y Business Analytics, ¿un caso asintomático?Trabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesishttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TPAnalítica de negociosOrganizacionesNegociosCOVID-19 (Enfermedad)Administración201614377Publication28321a14-cd39-4688-9e11-334dd6b38ebbvirtual::16326-1a6a5df4f-48ed-491c-8e84-406473e7d5dfvirtual::16327-128321a14-cd39-4688-9e11-334dd6b38ebbvirtual::16326-1a6a5df4f-48ed-491c-8e84-406473e7d5dfvirtual::16327-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000894710virtual::16326-1THUMBNAIL23798.pdf.jpg23798.pdf.jpgIM Thumbnailimage/jpeg10646https://repositorio.uniandes.edu.co/bitstreams/05c6d8dc-3793-4f34-90ef-c1c4727f3146/downloadcea8a1a1610255da9165837cd6dc6ac6MD55ORIGINAL23798.pdfapplication/pdf1330192https://repositorio.uniandes.edu.co/bitstreams/0de794cd-0945-4dc4-9e1d-59354927a339/download432647713a5165612b6c85b3ea8f7354MD51TEXT23798.pdf.txt23798.pdf.txtExtracted texttext/plain126041https://repositorio.uniandes.edu.co/bitstreams/db6bf81c-ec03-4e18-8c4c-5e4374f08f78/downloadc3dc95d07cf33a3563ace1bfba820017MD541992/51047oai:repositorio.uniandes.edu.co:1992/510472024-03-13 15:41:53.498http://creativecommons.org/licenses/by-nc-nd/4.0/open.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co |