Start browsing through R tutorials online and it won't take long to stumble across a read.csv statement. CSV files serve well for detached, static analyses. They tend fail, however, when tasked with storing large, dynamic data sets being accessed interactively by globally dispersed, concurrent users. Often the go to in this situation is a traditional relational database management system such as Oracle or MySQL, but there are other options! This talk will review the various back-ends, along with potential considerations, Merck's Digital Proactive Process Analytics group has implemented to support various Shiny applications, dashboards, and automated data analysis pipelines.
Marcus Adams
Merck
Its Not Whats on the Outside, but Its Whats on the Back-end That Matters: The World Beyond CSV Files
Start browsing through R tutorials online and it won't take long to stumble across a read.csv statement. CSV files serve well for detached, static analyses. They tend fail, however, when tasked with storing large, dynamic data sets being accessed interactively by globally dispersed, concurrent users. Often the go to in this situation is a traditional relational database management system such as Oracle or MySQL, but there are other options! This talk will review the various back-ends, along with potential considerations, Merck's Digital Proactive Process Analytics group has implemented to support various Shiny applications, dashboards, and automated data analysis pipelines.