Gartner Magic Quadrant Data Science And Machine Learning Platforms
Data Science and Machine Learning platforms have become essential tools for organizations to make data-driven decisions. However, with so many platforms available in the market, it can be challenging to identify which tool is the right fit for your organization. To help you make an informed decision, Gartner, a research and advisory firm, has published the Magic Quadrant for Data Science and Machine Learning Platforms every year since 2014. In this article, we will discuss what the Gartner Magic Quadrant is, how it evaluates platforms, and some of the leading platforms in their 2021 report.
What is the Gartner Magic Quadrant?
The Gartner Magic Quadrant is a research methodology that helps organizations understand how different technology providers are positioned relative to each other in a particular market. In this case, the market is Data Science and Machine Learning Platforms. Gartner evaluates each vendor based on two main criteria:
- Completeness of Vision: This criterion looks at the vendor's ability to understand market trends and customer needs and to develop a roadmap that aligns with these trends and needs.
- Ability to Execute: This criteria evaluates the vendor's ability to deliver a product that meets customer needs with a high level of quality, support, and service.
Based on their evaluations, Gartner places each vendor in one of four quadrants:
- Leaders: These vendors have a strong market presence and a proven track record of delivering high-quality products and services. They also have a clear vision for the future of their product.
- Challengers: These vendors have a strong market presence, but they may lack a clear vision for the future of their product.
- Visionaries: These vendors have a clear vision for the future of their product, but they may lack a strong market presence or a proven track record of delivering high-quality products and services.
- Niche Players: These vendors have a limited market presence and may focus on a specific niche or vertical market.
Leading Platforms in the 2021 Gartner Magic Quadrant
The 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms evaluated 20 vendors. Here are some of the leading platforms:
Leaders
Alteryx
Alteryx is a self-service analytics platform that allows users to blend, prep, and analyze data from a variety of sources. It offers a wide range of data preparation and enrichment tools, as well as machine learning algorithms and predictive analytics capabilities.
IBM
IBM's Watson Studio is a cloud-based data science and machine learning platform that allows users to build, train, and deploy machine learning models. It offers a variety of tools for data preparation, model training, and deployment, as well as support for popular programming languages such as Python and R.
Challengers
MathWorks
MathWorks' MATLAB is a programming language and development environment for numerical computing, visualization, and machine learning. It offers a wide range of built-in functions and tools for data analysis, as well as support for deep learning and reinforcement learning.
RapidMiner
RapidMiner is a data science platform that offers a wide range of tools for data preparation, machine learning, and predictive analytics. It also offers a low-code interface that allows users to build and deploy machine learning models without writing any code.
Conclusion
The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is an invaluable resource for organizations looking to invest in a data science platform. By evaluating vendors based on their vision and ability to execute, Gartner provides a comprehensive overview of the market and helps organizations make informed decisions. Whether you're looking for a self-service analytics platform or a cloud-based machine learning platform, there is a platform out there that fits your needs.