Data is Art at the eyes of artist; and Science at the eyes of scientist; and vice verse.
Data presentation is meant to communicate information in a
way that resonates singularly with its intended audience, and it may require
technical/artistic skill to pull that off visually. Perhaps an interesting
question upon Big Data talent is: Do you need a scientific data artist or
artistic data scientist?
The data scientist
must be an effective communicator more so than an artist. But is not communication
itself an art? Yes it is! Do data scientists require creativity? Yes,
absolutely. Their creativity must be harnessed for asking new questions and
puzzling out logic to accomplish tasks in ways that are increasingly effective
and efficient - in measurable, accurate, scientific ways.
Being insightful,
that’s the ability needed for data talent. When talking about "big
data", so much of the narrative of its usefulness is around eliminating
subjective decision-making in favor of objective decision-making. The point is
that the ability to produce evidence must be connected somehow to the ability
to draw meaningful and actionable insights. Scientific data approach shall not
be overly rigid and artistic perspective also does not mean the subjective
discussion such as "beauty is in the eye of the beholder" and
"art for art's sake," etc.
Creative data
scientist and well trained data artist are both welcomed in the Big Data team.
The very vagueness in the definition of data science is the reason it opens the
door to so many disciplines. We all love the graphs and the visual display of
evidence, as it makes communicating results so much easier. But making graphs
that is visual and effective takes lots of practice and tedious work. The
majority of the data scientist's skills must be scientific skills, No matter
how beautiful a chart is, the business users who are looking at it need to know
that it is accurate and trustworthy - that was created through a scientific
process. If the data artist has the training, experience and good judgment to produce
informative graphs, then it would be a welcome addition to a data science team.
The team with well
mixed skills can perform the best. Scientific Data Artists are the folks
who have the training or experience to determine what is truly informative, what
relationship to display, as well as the methodological insight needed to know
how to deal with crucial aspects related to data (outliers/ extremes comes to
mind). One can display all sorts of "interesting" relationships from
the data. One way for such a role to be relevant and functional is that it
be integrated within a team of statisticians/data scientists so that it
can provide the needed guidance
Big Data talent, either you are artistic data scientist or
scientific data artist, need to have three ‘C’ qualities: Critical thinking to find patterns & challenge old knowledge; Curiosity to ask good questions and
puzzle out the business logic; as well as the Creativity to visualize and explore unknowns, and communicate well
to solve business problems.
2 comments:
Pearl, I am flattered you found my Dec. 18 post in the discussion at http://www.linkedin.com/groups/Data-Scientist-vs-Data-Artist-35222.S.5815890046594600960?view=&gid=35222&type=member&item=5815890046594600960&trk=eml-anet_dig-b_nd-pst_ttle-cn
to be a suitable launch pad for your article here. Clearly, the subject matter is of great interest to you, and we are in agreement about the need for relevance and functionality in any artistic endeavors produced by an analytics team.
.
Where you chose to use several of my key sentences word for word, however, professional courtesy dictates that quotation marks and attribution would have been appropriate.
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