Data Science vs. Analytics?
Originally published February 27, 2013
I came across the term “data scientist” a few years ago when somebody (from the valley, of course) asked me, “So are you a data scientist?" And my immediate answer was, “No, I am not a scientist." Although I already had spent a decade in the data space, driving business impact through analytics, I did not see myself as a scientist.
Figure 1: Aryng's BADIR Methodology
Today, data scientists are well trained, or perhaps over trained, on the blue track; but the green track often eludes them, mostly because it is not taught as a science in the universities. Nevertheless, green track is a science and is completely learnable (check out Aryng’s Data-to-Decisions Week – a week for complete hands-on education on analytics and testing – with green and blue tracks).
Unless an insight sees the light of the day by way of getting transformed into a decision, it is a complete waste of resources and time. Unless analytics drives business impact, it is not analytics. It is just statistics; it is just data science. That brings me back to the term data scientist, which sounds academic and all too blue track to me. To me, data science + decision science = analytics.
But again, words are just words. As long as both green track and blue track processes are followed, data will lend itself to decisions – call it data science or call it analytics.
Notes from the author:
For more details on blue and green tracks, which are part of BADIR – the 5-step process from “data to decisions,” feel free to download this white paper on BADIR. And if we can help your organization in the journey towards being data-driven, with green track married to blue track, feel free to contact us.
SOURCE: Data Science vs. Analytics?
Recent articles by Piyanka Jain, CEO of Aryng
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