Irene Steves | The dynamic duo: SQL & R | RStudio

There's a point in every data wranglers' career in which their full dataset can no longer fit into just CSV files, and the journey to database-world begins. I reached this point about two years ago, when I transitioned from ecological research to the world of eCommerce fraud prevention. My calls to read_csv became scarcer as I came to rely more and more on databases. In this talk, I'll demonstrate how I use R and SQL to access database tables, and how I incorporate both into my daily workflow, aided by features in RStudio IDE. I'll also discuss our company’s "riskiconn" package for handling database connections and queries, which includes customizations to simplify day-to-day data querying.
About Irene:
Irene holds an M.Sc. in Ecology and a B.A. in Integrative Biology, through which she first discovered R and data science. Her interest in data led her to the Arctic Data Center at the University of California Santa Barbara, a summer internship at RStudio, and ultimately to the Research & Data Science department at Riskified, where she now explores the complex patterns of fraud in eCommerce. In her free time, she studies Hebrew through podcasts and dubbed kids' movies.

[@TURALOWEN]

Hi Irene! My story is very similar. I have been using R/R Studio and tidyverse for a long time, but never dealt with databases or SQL. Your video DID convince me to actually learn SQL and be bilingual. Thank you!

[@olivermoser197]

Thank you so much. I am quiet into dplyr but had no practical experience with databases like you, so I never really understood why I should learn SQL especially while the syntax looks so much more complicated and less powerful to me. Your video helped me a lot!

[@OscarRodriguez-lf8bp]

Gracias por contar vuestra experiencia..!! Thanks you for sharing Your experiencie with us.!! It was helpful for me.!!

[@multitaskprueba1]

Fantastic lecture! Thank you!

[@haraldurkarlsson1147]

It is not surprising that there is overlap between dplyr and SQL. After all SQL influenced the design and structure of dplyr.