Citas bibligráficas
Viteri, A., Beltrán, J. (2023). Solución de big data para el análisis de los datos abiertos de MINSA y CENARES para el monitoreo y control de la emergencia sanitaria covid-19 bajo el ecosistema de Apache Hadoop y Microsoft Azure [Tesis, Universidad Privada Antenor Orrego - UPAO]. https://hdl.handle.net/20.500.12759/10283
Viteri, A., Beltrán, J. Solución de big data para el análisis de los datos abiertos de MINSA y CENARES para el monitoreo y control de la emergencia sanitaria covid-19 bajo el ecosistema de Apache Hadoop y Microsoft Azure [Tesis]. PE: Universidad Privada Antenor Orrego - UPAO; 2023. https://hdl.handle.net/20.500.12759/10283
@misc{renati/374422,
title = "Solución de big data para el análisis de los datos abiertos de MINSA y CENARES para el monitoreo y control de la emergencia sanitaria covid-19 bajo el ecosistema de Apache Hadoop y Microsoft Azure",
author = "Beltrán García, José Antonio",
publisher = "Universidad Privada Antenor Orrego - UPAO",
year = "2023"
}
Big Data has played an important role in the response to COVID-19. The first alarm about this new virus was given on December 31, 2019 thanks to the tracking with Big Data and Artificial Intelligence - from the company BlueDot. Since the Covid-19 spread, in China an attempt was made to decrease or detect the number of infected people through the collection of data from those infected, then they generated a number of applications to inform people about the cases and the severity . Big Data solutions and their correct use can be a very useful tool for detection and thus lower the contagion curve against COVID-19. The National Center for the Supply of Strategic Health Resources (CENARES), as a Decentralized Organization of the Ministry of Health, is in charge of managing the supply of strategic health resources, prioritized through national requests, developing the necessary mechanisms for the care of the health interventions defined by the programs of the Ministry of Health - MINSA. The problem with these institutions is that currently the variables that must be taken into account to make a more accurate projection of the amount of vaccines and implements that must be purchased and distributed, according to the region, province and / or have not been identified. District. The work aims to build a solution based on data collected from different sources (MINSA-CENARES), which will allow to analyze, understand and monitor the information to optimize the purchase and distribution of vaccines and implements against COVID-19 under the Apache ecosystem. Hadoop and Microsoft Azure.
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