We will tackle data transformation/ETL, statistics and visualisation/presentation later, but the first goal is to solve the “How can I get data” problem.

The current strategy is to introduce the team to R and train everyone up in running simple scripts that download the data they need for their reports. Downloading data and creating reports is a big time-sink that looks ripe for optimisation. IIH Nordic have an aim to introduce a 4-day work week within a couple of years, so the motivation is to find out how to save 20% of the current work schedule without harming productivity. I’ve just started a new job at IIH Nordic where a part of my duties is to look for ways to automate the boring tasks that come up in a digital web analytics team. Motivation: In search of a 4-day work week If you have any suggestions on improvements please tweet to me at or email via the blog. It is inspired by conversations with and on twitter about this kind of setup, and was useful to me as a way to organise my thoughts on the subject ).

A shared cron folder that runs every day at 0630 that user’s can put their own scripts into.

Restart the server to securely load private Github R packages / Docker images.

RStudio Server instance with multiple login.

This blog will give you steps that allows you to run on Google Compute Engine a server that has these features: Here is a post on getting started with it. Edit 20th November, 2016 - now everything in this post is abstracted away and available in the googleComputeEngineR package - I would say its a lot easier to use that.

Google cloud rstudio