dm bridges the gap in the data pipeline between standalone data frames and relational databases. Implementing a "grammar of joined tables", it provides a consistent set of verbs for consuming, creating, and deploying relational data models. In this talk I present a short overview of how dm can help your data analysis and ETL processes, and highlight recent developments.
Talk materials are available at https://github.com/rstudio/rstudio-conf/blob/master/2022/kirillmuller/dm-rstudioconf2022.pdf/.
Kirill has been working on the boundary between data and computer science for more than 20 years. He has been awarded five R consortium projects to improve database connectivity and performance optimization in R. Kirill is a core contributor to several tidyverse packages, including dplyr and tibble. He holds a Ph.D. in Civil Engineering from ETH Zurich and is a founder and partner at cynkra.
