So, after all it wasn’t such a ‘razor tight’ presidential race last night. Not that the Big Data camp expected one in the first place. Nate Silver, the poster child of predictive analytics in the political arena made a pretty convincing case for why Obama was very likely to win; he actually quantified it at around 90% probability. Just for kicks, compare this to Kimberley Strassel at the WSJ who in all earnest made the case for Romney just one day before the election.
In short, independent of the political outcome of this election it’s a yet another great showcase where Big Data wins hands down over punditry!
P.S. if you don’t have a WSJ.com subscription you can also get a copy of Strassel’s—well, what am I going to call it? Article?
theory in practice 
The key assumption in Nate’s analysis is that the polls are reasonably accurate. And it turned out this assumption held well – sampling works indeed!
Yes, you’re absolutely right! Know your input data :-)
Interesting article on Romney’s campaign not believing in the polls:
http://www.slate.com/articles/news_and_politics/politics/2012/11/why_romney_was_surprised_to_lose_his_campaign_had_the_wrong_numbers_bad.html
(the URL itself may also be the funniest I’ve seen during this election season)