So what should be in the toolkit of people who call themselves a data scientist?
A fundamental skill is the ability to manipulate data. A data scientist should be familiar and comfortable with a number of platforms and scripting tools to get the job done. What is difficult in Excel might be trivial in R. And when R struggles, you should switch to Unix (or use a programming language such as Python) get that portion of the data munging done. Along the way, you pick up a lot of tips and tricks. For example: how to read a big datafile in R?
The goal is to get the job done. Familiarity with a wide variety of tools, and expertise in some is the hallmark of any good would-be data scientist.
Wednesday, December 7, 2011
Friday, December 2, 2011
The Books and Video included in the set are:
- Data Analysis with Open Source Tools
- Designing Data Visualizations
- An Introduction to Machine Learning with Web Data (Video)
- Beautiful Data
- Think Stats
- R Cookbook
- R in a Nutshell
- Programming Collective Intelligence