By: Richard Boire, Founding Partner, Boire Filler Group
In our Big Data world, software applications and programming tools continue to expand the data scientist’s toolkit in facilitating the process of building predictive analytics solutions. Open-source tools have become much more prevalent in the last few years as they enable access to this discipline to a much wider array of people thereby providing much more potential for knowledge enhancement. The academic world and young students are now focusing their intellectual energies in developing new processes and techniques that are improving all facets of our everyday life. Using data science as the foundation, new tools have evolved that allow easier flexibility in being able to function within the semi-structured and unstructured world of Big Data. Such tools as Python, R, Pig, Mahout.etc. represent just some of the newer tools in the data scientist’s arsenal along with perhaps SAS which still remains the dominant commercial data science application according to most benchmark studies.