In his excellent article on the rise of the Data Scientist, Nathan of Flowing Data writes:
Even if you’re not into visualization, you’re going to need at least a subset of the skills […] if you want to seriously mess with data. Statisticians should know APIs, databases, and how to scrape data; designers should learn to do things programmatically; and computer scientists should know how to analyze and find meaning in data.
There are many more nuggest of insight in his post, and I fully agree with him, that - what he terms - Data Scientists will become increasingly important.
I have lately been talking a lot about “IA for the Layman”, my idea that certain skills will have to become common teaching, so people will be able to cope with the increasing tides of data in their personal life.
But IA may be the wrong term, or rather an oversimplification in this context. As Nathan mentions, Ben Fry covers quite well what skills are actually involved and how they form different aspects. So maybe I shouldn’t call it “IA for the Layman”, but rather “Be Your Personal Data Scientist”.