Astronomy, like many other sciences, is heavily reliant on data analysis. Scientists looking at stars and planets record a multitude of variables including heat signatures, brightness levels, radiation, and even high level chemistry equations. As a result, it’s not too difficult to see how scientists make discoveries much later than the data shows.
In 2009, the space observatory, Kepler, named for early astronomer Johannes Kepler, was launched with the mission of discovering more exoplanets. Exoplanets are Earth-like planets that orbit stars outside of our solar system. Kepler was extraordinary at its job, almost too good in fact. Using a photometer that monitors the brightness of almost 150,000 stars, as of February of 2014 Kepler has discovered over 900 confirmed planets as well as another 3600 unconfirmed.
Discovering 900 planets out of over 4000 candidates is no small feat, but on February 26, 2014 scientists discovered an astounding 715 new planets from the Kepler’s old existing data via big data analysis. Using a tool called ‘verification by multiplicity’ NASA scientists were able to comb through overwhelming amounts of data with pinpoint accuracy. This sophisticated big data technique has roots partly based in probability and can be used for “wholesale validation” according to Jason Rowe, a member of SETI (Search for Extraterrestrial Intelligence).
Thanks to big data analysis, a groundbreaking astronomical discovery has been made. The next question though is “How do we apply this to the business world?” A giant space observatory returning an overwhelming amount of data is not that far off from a company with millions of customers. Using this same principles one could glean industry insights that are invaluable to any company’s success.