Work Regulated Environments Big Data Applications Cloud Infrastructure R in Production What is there to learn? What are the needs? What can we build? The R for Data Science Workflow Drops in Solutions Engineers!
deployment lead time How long does it take you to get from raw materials (data) to some kind of finished product? How many teams do you have to traverse to make a real impact with the product of your work?
enables teams to deliver value through decreasing code deployment lead time 2. Architecture dominates how daily work is performed The improvement of daily work is more important than daily work itself Possibly from the DevOps handbook?? - Gene Kim @RealGeneKim
Onboards new tools, deploys solutions, supports existing standards Works closely with IT to maintain, upgrade and scale analytic environments Influences others in the organization to be more eﬀective Passionate about making R a legitimate analytic standard within the organization Check out Nathan Stephens on the RViews Blog - Analytics Administration for R
Grad School: RStudio IDE (local) + shinyapps.io (free account) My first “real” engineering job: - AWS Cloud $ - Open Source RStudio and Shiny Server (free!) Solutions Engineer: - All the clouds, all the products - limited by imagination (privileged)
force yourself to become an R Admin if the work is tedious to you. But also don’t ignore it. Getting the right tools matters. Seek out an analytic administrator or encourage that growth in someone around you.