How Did American Voters Prove All The Data

Pundits Wrong?

While the world of American politics is not a stranger to the field of big data, what with Barack Obama’s presidential victory, proving to be the foreground for the win of big data in accurately predicting the results of that iconic election. But when it came to the 45th Presidential Election Of The united States Of America, the tables were turned over resulting in exactly opposite circumstances of what was being predicted. How did this contradictory turn of events come to be? In spite of so many experts all over the world, reiterating Hillary Clinton’s victory time and again, it was utterly mind boggling to see the popular opinion back up Donald Trump, resulting in his sweeping victory.

Going into the technicalities of this scenario, one can refer to a very popular theory in the field of computer science, this theory is “garbage in, garbage out”; this basically goes on to highlight the negative aspects of bad data. For instance, when it comes to mega giants of the world of technology like Facebook and Google; both these companies use clean, refined data to feed into their algorithms, which helps their computers accurately recognize even a cat. That’s probably is something that did not happen during the elections this time, as a lot of experts believe that data crunching can be only as good as the data being used and would be entirely pointless if bad data was involved. While companies like these are able to work with this clean data, but when it comes to polling data, it is an entirely new dynamic. In terms of the recently concluded US election, the leading daily Washington Post reported that the data analytics, used by Hillary Clinton’s team was a custom algorithm called Ada. This basically helped her

team figure out where best could they dedicate their resources on the basis of the polling numbers. On the other hand Trump’s team relied more on the primitive methods, when it came to distributing their resources. Instead of depending on the poll numbers, they decided to take decisions based on the emotions of the audiences at his rallies and other other campaign events. Doing this actually resulted in Trump’s victory in Pennsylvania, where the polls has initially predicted Hillary to win. In spite of being

so accurate in nature, polling data at its very core, is based on the person’s honesty. Another fact to be noted here, is that most of those who support Trump have a deep seated apprehension towards the national media and also have intense suspicion towards Hillary Clinton. While there are a lot of theories based on this surprising turn of events, where the poll data actually might have been the bad data that the data analytics industry warns all about. These ‘undercover trump voters’ or basically people who did support Trump but lied to the polls about supporting Hillary, could have been the potential game changers in this year’s elections. While speculations are rife as to how could so much data be misleading, one thing is sure that America has made their choice and elected Donald Trump as the most powerful person in the world. Both the presindential candidates had an expert team of data analytics professionals, who helped them in devising their respective campaigns. With the growing popularity of this industry, more and more people are looking to get trained in data analytics. This has sparked the presence of many training like Imarticus Learning offering courses in various tools of data analytics like R Programming, SAS Programming, Hadoop and so on. Stay tune with us for updated news: Twitter Linkedin Facebook