Vendors Eye Citizen Data Scientists
January 17, 2017
than 40 percent of data science tasks will be automated by 2020,
resulting in increased productivity and broader usage of data and
analytics by citizen data scientists.
Gartner defines a citizen data scientist as a person who creates or
generates models that use advanced diagnostic analytics or
predictive and prescriptive capabilities, but whose primary job
function is outside the field of statistics and analytics.
According to Gartner, citizen data scientists can bridge the gap
between mainstream self-service analytics by business users and the
advanced analytics techniques of data scientists. They are now able
to perform sophisticated analysis that would previously have
required more expertise, enabling them to deliver advanced analytics
without having the skills that characterize data scientists.
With data science continuing to emerge as a powerful differentiator
across industries, almost every data and analytics software platform
vendor is now focused on making simplification a top goal through
the automation of various tasks, such as data integration and model
"Making data science products easier for citizen data scientists to
use will increase vendors' reach across the enterprise as well as
help overcome the skills gap," said Alexander Linden, research vice
president at Gartner. "The key to simplicity is the automation of
tasks that are repetitive, manual intensive and don't require deep
data science expertise."
Mr. Linden said the increase in automation will also lead to
significant productivity improvements for data scientists. Fewer
data scientists will be needed to do the same amount of work, but
every advanced data science project will still require at least one
or two data scientists.
Gartner also predicts that citizen data scientists will surpass data
scientists in the amount of advanced analysis produced by 2019. A
vast amount of analysis produced by citizen data scientists will
feed and impact the business, creating a more pervasive
analytics-driven environment, while at the same time supporting the
data scientists who can shift their focus onto more complex
organizations don't have enough data scientists consistently
available throughout the business, but they do have plenty of
skilled information analysts that could become citizen data
scientists," said Joao Tapadinhas, research director at Gartner.
"Equipped with the proper tools, they can perform intricate
diagnostic analysis and create models that leverage predictive or
prescriptive analytics. This enables them to go beyond the analytics
reach of regular business users into analytics processes with
greater depth and breadth."
According to Gartner, the result will be access to more data
sources, including more complex data types; a broader and more
sophisticated range of analytics capabilities; and the empowering of
a large audience of analysts throughout the organization, with a
simplified form of data science.
"Access to data science is currently uneven, due to lack of
resources and complexity not all organizations will be able leverage
it," said Mr. Tapadinhas. "For some organizations, citizen data
science will therefore be a simpler and quicker solution their best
path to advanced analytics.