Getting things logged

One of the greatest strength of R is the ease and speed of developing a prototype (let it be a report or dashboard, a statistical model or rule-based automation to solve a business problem...

Getting things logged

January 30, 2020

One of the greatest strength of R is the ease and speed of developing a prototype (let it be a report or dashboard, a statistical model or rule-based automation to solve a business problem etc), but deploying to production is not a broadly discussed topic despite its importance. This hands-on talk focuses on best practices and actual R packages to help transforming the prototypes developed by business analysts and data scientist into production jobs running in a secured and monitored environment that is easy to maintain -- discussing the importance of logging, securing credentials, effective helper functions to connect to database, open-source and SaaS job schedulers, dockerizing the run environment and scaling infrastructure.

About the speaker

Gergely Daroczi

Gergely Daróczi is an enthusiast R user and package developer, Ph.D. in Sociology, former assistant professor and founder/CTO of an R-based web reporting application at rapporter.net, ex Lead R Developer & Research Data Scientist, then Director of Analytics at CARD.com, currently working as the Senior Director of Data Operations at System1 with a strong interest in designing a scalable data platform built on the top of R, AWS and various APIs. He maintains some CRAN packages mainly dealing with using R in production (automated reports, logging, database connections, API integrations), co-authored a number of journal articles in social and medical sciences, and wrote a book on "Mastering Data Analysis with R".