Gergely Daroczi | Getting things logged | RStudio (2020)
One of the greatest strengths 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
rstudio
Rstudio::conf(2020)
Gergely Daroczi
RStudio
Data Science
Machine Learning
Python
Stats
Tidyverse
Data Visualization
Data Viz
Ggplot
Technology
Coding
Connect
Server Pro
Shiny
Rmarkdown
Package Manager
CRAN
Interoperability
Serious Data Science
Dplyr
Forcats
Ggplot2
Tibble
Readr
Stringr
Tidyr
Purrr
Github
Data Wrangling
Tidy Data
Odbc
Rayshader
Plumber
Blogdown
Gt
Lazy Evaluation
Tidymodels
Statistics
Debugging
Programming Education
Rstats
Open Source
Oss
Reticulate
