More than 40% of Data Science tasks will be automated in 2020

 

Gartner claims that more than 40% of Data Science tasks will be automated by 2020, resulting in increased productivity and greater use of Data and Analytics by citizen data scientists.
 
This type of professional is defined by Gartner as a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but who has a primary job role outside the field of statistics and data analysis.
 
According to Gartner, citizen data scientists can bridge the gap between the traditional self-service analytics used by business users and the advanced analytics techniques of data scientists. They are able to perform sophisticated analytics that previously required more knowledge, providing advanced analytics without having the skills that characterize data scientists.
 
With Data Science emerging as a significant differentiator in industries, most Data and Analytics software platform providers are now focused on making simplification their primary goal by automating various tasks such as data integration and building models.
 
“Making Data Science products easier for citizen data scientists to use will increase the reach of suppliers across the enterprise and help overcome skills gaps. The key to simplicity is automating tasks that are repetitive, manual intensity, and not requiring in-depth knowledge of this science," explains Alexander Linden, vice president of Research at Gartner.
 
Linden says that increased automation will also provide significant productivity improvements for data scientists. Few professionals will be needed to do the same amount of work, but each advanced Data Science project will still need at least one or two scientists.
 
Gartner also predicts that citizen data scientists will outpace data scientists in the amount of advanced analytics produced by 2019. Many materials produced by citizen data scientists will feed and impact businesses, creating a more comprehensive Analytics-driven environment, while at the same time , will support traditional practitioners who can shift their focus to more complex analysis.
 
“Most organizations don't have enough data scientists that are consistently available in the business, but they do have many qualified information analysts who could become citizen data scientists,” says Joao Tapadinhas, Research Director at Gartner. “Equipped with the appropriate tools, they can perform complex diagnostic analytics and build models that leverage predictive or prescriptive analytics. This allows them to go beyond the reach of common business data analysis to processes with greater depth and breadth.”
 
According to Gartner, the result will be access to more data sources, including more complex types, a range of broader and more sophisticated analytic capabilities, and the empowerment of a large audience of analysts across the organization with a streamlined form of data. Data Science.
 
Currently, access to Data Science is uneven due to lack of resources and complexity. Not all companies will be able to leverage it. For some organizations, citizen data science will therefore be a simpler and faster solution. The best way for advanced Analytics”, completes Tapadinhas.