Imag\u00ednate, en unos d\u00edas ser\u00e1 Navidad. Est\u00e1s trabajando en esta compa\u00f1\u00eda de tecnolog\u00eda que ofrece soluciones de movilidad y tu jefe te pide que estimes la demanda de carreras que recibir\u00e1n durante esa noche. Tu sentido com\u00fan te dir\u00e1 que habr\u00e1 m\u00e1s gente que necesite trasportarse del aeropuerto a su casa y que habr\u00e1 menos solicitudes durante la hora pico. (No es claro si Pap\u00e1 Noel vaya a usar sus servicios). Tienes que decidir si usas los datos hist\u00f3ricos de la base de datos de tu compa\u00f1\u00eda, en la que se han invertido importantes recursos, para tratar de identificar si hubo alg\u00fan patr\u00f3n durante las pasadas Navidades.<\/p>\n
Este es el tipo de proyecto anal\u00edtico en el que me desempe\u00f1\u00e9 cuando estaba realizando mi pasant\u00eda en China en una compa\u00f1\u00eda de transporte de econom\u00eda compartida. Lo siguiente que sucedi\u00f3 es que encontr\u00e9 varias variables que serv\u00edan como determinantes de la demanda \u2013temperatura, humedad, la hora del d\u00eda o de la noche, si era entre semana o en fin de semana, entre otros. Constru\u00ed una regresi\u00f3n para explicar c\u00f3mo y qu\u00e9 tanto cada uno de estos factores impactaban el n\u00famero de solicitudes de viajes recibidas. Con el modelo logramos establecer el n\u00famero aproximado de solicitudes que tendr\u00edamos y por tanto una estrategia para balancear la oferta y la demanda en esa fecha.<\/p>\n
Este tipo de problemas es a los que se enfrenta diariamente el mundo de los negocios. Business Analytics<\/em> es la clave para resolver preguntas poco convencionales en el mundo de los negocios. C\u00f3mo Facebook te recomienda a las personas que quiz\u00e1s conozcas, c\u00f3mo LinkedIn encuentra a alguien con un perfil similar al tuyo, c\u00f3mo FedEx puede predecir cu\u00e1ndo te llegar\u00e1 tu paquete, c\u00f3mo Uber dise\u00f1a la mejor ruta para tu viaje. Data Scientists<\/em> usa la programaci\u00f3n como una herramienta que unida a su comprensi\u00f3n de los negocio, explica el pasado de la mejor manera y predice el futuro m\u00e1s acertadamente. A partir de lo que parece una informaci\u00f3n ca\u00f3tica y desordenada se encuentran oportunidades de negocios.<\/p>\n El \u201cancho de banda\u201d del cerebro humano es limitado, no puede procesar demasiada informaci\u00f3n al mismo tiempo. Igualmente, como humanos, nuestro juicio est\u00e1 sesgado. La tecnolog\u00eda est\u00e1 cambiando todos los aspectos de nuestra vida y nos puede abrumar con informaci\u00f3n, podemos buscar ayuda en los computadores. Viniendo de una formaci\u00f3n en negocios, me alegra haber encontrado el MSBA de Emory University que abre un mundo de oportunidades en el campo del an\u00e1lisis. Este programa STEM de 10 meses me da las herramientas t\u00e9cnicas necesarias para ser un Data Scientist, al tiempo que la formaci\u00f3n en negocios asegura que pueda aplicar las herramientas aprendidas en el mundo real.<\/p>\n \u00danete a nosotros para trasformar informaci\u00f3n en herramientas para la toma de decisiones<\/p>\n Yan Li<\/strong> Why I chose to pursue the MS in Business Analytics Program at Emory University\u2019s Goizueta Business School?<\/strong><\/p>\n Imagine this, a few days later it is going to be the Christmas. You are working in this ridesharing company and your boss is asking you to figure out how many ride requests there will be on Christmas Eve. Your common sense is telling you there will be more people who need a ride home from the airport while there will be much fewer commuters sending ride requests during rush hours (not sure if Santa is going to use your services or not though). Then you figure if you should pull up the historical data from the fancy database your company have already spent millions of dollars on and try to see if there\u2019s a certain pattern during last year\u2019s Christmas.<\/p>\n This is the predictive analysis project I ran into when I was an intern at this ridesharing company in China. What would usually happen next was I found several predictors \u2013 temperature, humidity, hour of the day, if it\u2019s weekday or weekend, if it is holiday or not, discount, and etc, and I built a regression model to explain how and how much these factors would change the number of requests we received every day. With the predicted number of requests on hand, now we can adjust the coupon strategy to balance the demand and supply accordingly.<\/p>\n Problems like this are everywhere in today\u2019s business world \u2013 how Facebook recommends to you people you may know, how LinkedIn finds someone who has the similar career path, how FedEx knows when your package will be delivered, how Uber designs the best route for carpool. Business analytics is the key to all these unconventional business questions. Business data scientists use data programming as a tool in addition to their business understanding to better explain the past and predict the future. From the seemingly chaotic data, we disclose hidden business growth opportunities.<\/p>\n Human brains\u2019 bandwidth is limited \u2013 we just cannot process too much information at the same time. Human judgement is always biased as well. As technology reshapes every aspect of our life and causes information overload, let\u2019s just ask computers for help. Coming from a business background, I\u2019m glad I found this MSBA program at Emory University that opens up a world of opportunity in the analytics field. This 10-month STEM designated program perfects my technical skills for a future business data scientist. Meanwhile, the business nature of this program ensures me I can seamlessly apply these skills in real-world practices.<\/p>\n","protected":false},"excerpt":{"rendered":" Imag\u00ednate, en unos d\u00edas ser\u00e1 Navidad. Est\u00e1s trabajando en esta compa\u00f1\u00eda de tecnolog\u00eda que ofrece soluciones de movilidad y tu jefe te pide que estimes la demanda de carreras que recibir\u00e1n durante esa noche. Tu sentido com\u00fan te dir\u00e1 que habr\u00e1 m\u00e1s gente que necesite trasportarse del aeropuerto a su casa y que habr\u00e1 menos […]<\/p>\n","protected":false},"author":8,"featured_media":29392,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","content-type":"","_joinchat":[],"footnotes":""},"categories":[31,41],"tags":[],"class_list":["post-29391","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-europa","category-mba-contact-fair"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/posts\/29391","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/comments?post=29391"}],"version-history":[{"count":0,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/posts\/29391\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/media\/29392"}],"wp:attachment":[{"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/media?parent=29391"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/categories?post=29391"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thegradschool.com\/site\/wp-json\/wp\/v2\/tags?post=29391"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nUna contadora de historias apasionada y amante de los n\u00fameros
\nque cree en el poder de la toma de decisiones gerenciales basadas
\nen informaci\u00f3n cuantitativa.
\nM.S. Business Analytics<\/strong>, Class of 2019
\nGoizueta Business School, Emory University
\nB.A. in Finance, Women Who Code, Lean In China
\nhttp:\/\/www.linkedin.com\/in\/yan-li<\/strong>
\nyan.li2@emory.edu<\/em><\/p>\n