Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on Cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities.When choosing the best one, organizations often trust on The Gartner Magic Quadrants which aims to provide a qualitative analysis into a market and its direction, maturity and participants. Gartner previously called these platforms “advanced analytics platforms”. But since this platform is primarily used by “data scientists“ so from this year the Quadrant has been renamed to Magic Quadrant for Data Science Platforms.
This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solution. These platforms are used by data scientists for demand prediction, failure prediction, determination of customers’ propensity to buy or churn, and fraud detection.
The report aims to rank the BI platforms on the ability to execute and the completeness of vision. The Magic Quadrant is divided in 4 parts:
- Niche Players
Adoption of open-source platforms and Diversity of tools is an important characteristic of this market. IBM’s mission is to make data simple and accessible to the world and commitment to open source and numerous open-source ecosystem providers made it most attractive platform for Data Science.