Gartner predicts that by 2020, predictive and prescriptive analytics will attract 40% of enterprises' net-new investment in the overall business intelligence and analytics market. It also expects that more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.
According to Gartner, end-user organizations are reporting a wide range of data science projects that incorporate three major use cases: business exploration, advanced prototyping and production refinement. These diverse operations often drive platform selection and the mix of technologies chosen.
The Gartner Critical Capabilities for Data Science and Machine Learning Platforms 2018 report evaluated 16 vendors across 15 critical capabilities spanning three use cases.
If you want to go beyond academics and transform your data science initiatives into economics, this evaluative report is a must-read.