Cały artykuł znaleźć można tutaj:
http://dataspora.com/blog/sexy-data-geeks/
W skrócie:
Skill #1: Statistics (Studying). Statistics is perhaps the most important skill and the hardest to learn. It’s a deep and rigorous discipline, and one that is actively progressing (the widely used method of Least Angle Regression was only recently developed in 2004). I expect to be on its learning curve my entire life. This being the case, people who possess a solid grasp of modern statistics are rare. And yet problems that require its application continue to multiply. The text that I was exposed to in graduate school and find to be an unparalleled survey is Hastie, Tibshirani, and Friedman’s Elements of Statistical Learning.
Skill #2: Data Munging (Suffering). The second critical skill mentioned above is “data munging.” Among data geek circles (you can find us with a Twitter search for #rstats), this refers to the painful process of cleaning, parsing, and proofing one’s data before it’s suitable for analysis. Real world data is messy. At best it’s inconsistently delimited or packed into an unnecessarily complex XML schema. At worst, it’s a series of scraped HTML pages or a thoroughly undocumented fixed-width format.
Skill #3: Visualization (Storytelling). This third and last skill that Professor Varian refers to is the easiest to believe one has. Most of us have had exposure to basic chart-making widgets of Excel (and to date myself, tools like Harvard Graphics). But a little knowledge is a dangerous thing: these software tools are often insufficient when faced with the visualization of large, multivariate data sets.