Title: Automation of Data Analysis in AWS

Description:

Cloud computing and the advancement of tools for resource management and infrastructure automation have created unconventional forms of processing massive amounts of data, both efficiently, reliably and cost effectively. The effects of cloud computing can be visible in everyday life. Academic research is one of the fields that can benefit greatly from cloud computing. Particularly, genomics projects have successfully adopted cloud computing in research, and some start-ups have been created to offer services for mapping gene information to find links to pathologies by using AWS. Beyond genomics research projects, there is a vast amount of geospatial, satellite imagery, weather, news and other types of data available for analysis (https://aws.amazon.com/public-data-sets). To date, most compute intensive research tasks are run in supercomputers; the implementation of cloud computing has not been as fast as in other areas. Here it is proposed the utilization of AWS to analyze a set of data, automating the deployment of infrastructure and trigger analysis when a set of data is uploaded. This example shows scalability and elasticity of public clouds and can be easily applied to other types of analytics.