Gartner: More Than 40 Percent of Data Science Tasks Will Be Automated by 2020

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The Predicts 2017: Analytics Strategy and Technology report also predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis produced by 2019.

A new report by Gartner predicts that more than 40 percent of data science tasks will be automated within the next three years. This is expected to increase productivity and usage of data and analytics by citizen data scientists.

The company stated that they define a citizen data scientist as someone who creates or generates models that use analytics but whose primary job falls outside that field. They believe citizen data scientists can fill in the gap between the self-service analytics used by businesses and the advanced analytics used by data scientists. With this in mind, data and analytics platform providers are now making simplification and ease of use a top priority. Automating data integration, model building and other tasks should help.

“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 also stated that automation will lead to a significant rise in productivity for data scientists, resulting in few scientists being needed to do the same amount of work. He was quick to add that every data science project will still need at least one or two scientists.

The report also predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis generated within the next two years. Most of this analysis will feed businesses and impact decision-making, allowing data scientists to concentrate on more complex analysis projects.

“Most 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.”

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Sue Walsh

About Sue Walsh

Sue Walsh is News Writer for RTInsights, and a freelance writer and social media manager living in New York City. Her specialties include tech, security and e-commerce. You can follow her on Twitter at @girlfridaygeek.

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