Data scientists - the so-called "high-priests" of big data - combine unique and esoteric skills. Part intuitive artist, part statistical modeler and part programmer, the practitioner of this new art of research must be able to detect and make sense out of patterns hidden within millions upon millions of pieces of constantly streaming, completely unstructured data.
He or she must also must be able to smooth and clean the data, ask the right questions about that data, make valid inferences from the data as to how consumers and markets behave, and create statistical models with which to pinpoint behavioral triggers which prove or disprove their theories.
Jonathan Goldman, who administered the data science team behind LinkedIn's highly successful "People You May Know" button, notes that data scientists are sometimes referred to as "unicorns" simply because the combination of skills and talents required to do their job is so rare and hard to find.
In Unicorns Among Us, Lars Nielsen lays out the brief history of data science since its beginnings not long ago in this century. He as well explores the evolution of the role of the data scientist through this same period, and explores the best qualifications, the tools, the techniques, and the training involved in the practice of this arcane discipline.
Nielsen's audiobook will prove indispensable for anyone contemplating a career in this lucrative area, as well as any novice tasked to work with a data science team.
©2014 New Street Communications, LLC (P)2014 New Street Communications, LLC
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"Perfect for laymen & would-be data scientists"
Excellent information cogently presented.
Good delivery, enjoyable.
This was an hour or so of well-spent listening. Learned much. Very useful.
Excellent, easy and enjoyable tutorial on the Zen of data science and the professionals who practice that Zen - what they do, and how and why they do it. Data Science is a nuanced craft, and this nuanced exposition delivers a firm understanding such as will prove of special value to non-techies (and, for that matter, would-be data scientists). Highly recommended.
"First Few Chapters Are the Best"
Too much of the book focused on a specific software that for a while I forgot I was listening to a book about data scientists, as the title suggested.
"pretty boring missed its opportunity in actual insights and value by example"
talks mostly about the tools and history without actually describing real world examples and real insights
"Last chapter is the best chapter"
The last chapter discussed what isn't captured by the "unicorn's way of thinking. I found that to the most interesting aspect of the book.
"Data Scientist role overview"
Some sparks of insight probably worth the price of admission. Some parts that sound like an excel spreadsheet being read with feeling. I had hoped for something more substantial.
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