R is a great environment for interactive analysis on your desktop, but when your data needs outgrow your personal computer, it's not clear what to do next.

This is material for a short overview of scalable data analysis in R. The slides can be viewed at https://ljdursi.github.io/beyond-single-core-R .

It covers:

• How to think about parallelism and scalability in data analysis
• The standard parallel package, including what was the snow and multicore facilities, using airline data as an example
• The foreach package, using airline data and simple stock data;
• A summary of best practices.

Included in the materials, though not in the talk, are some more advanced methods:

• The bigmemory package for out-of-core computation on large data matrices, with a simple physical sciences example;
• The Rdsm package for shared memory; and
• a brief introduction to the powerful pbdR pacakges for extremely large-scale computation.