What Data Scientists Really Do, According to Data Scientists
&quot;The only difference between screwing around and science is writing it down&quot; - Adam Savage.<p>In all seriousness, why can&#x27;t data science simply be about applying the scientific method in the realm of data analysis?  It doesn&#x27;t need to be conflated with machine learning, BI, SQL, etc.  It can just be about approaching data analysis with scientific rigor.<p>My opinion is that the term data science evolved when we started needing cross-functional people who are a blend of:<p>- domain experts;<p>- numerical&#x2F;quantitative specialists (such as statisticians, mathematicians, physicists, STEM people);<p>- business analysts, business intelligence; and,<p>- those who traditionally deal with data management, platforms and tools.<p>That confluence of people was needed amidst the related trends:<p>- increased government funding for STEM education and brain research;<p>- marketing from companies such as IBM (&quot;Watson&quot;), the democratization of data and increase in the use of data in daily life;<p>- the big data wave, subsequent interest in &quot;internet of things&quot; and &quot;digital transformation&quot;;<p>- renewed interest in machine learning and AI (recurrent neural networks and other breakthroughs);<p>- and others of course..<p>We needed to apply more discipline to data analysis - thus data science was born.  A formalizing of what many were already doing, to capture the need and changing paradigm.  Or so I like to believe.