SAS a Leader in 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

Gartner has recognised SAS as a Leader in its 2019 Magic Quadrant for Data Science and Machine Learning Platforms. The report evaluated SAS for its completeness of vision and ability to execute. This is the sixth consecutive year SAS has been recognised as a Leader in this Magic Quadrant, making it the only enterprise provider to maintain this position.

"Machine learning is a vital asset to modern data scientists today” said Iain Brown, Head of Data Science at SAS UK & Ireland. “It enables businesses to not only identify opportunities, but also highlight any potential risks that may be overlooked by humans.”

“It’s also important that businesses have a platform that supports not only classic and modern machine learning algorithms but the entire analytics lifecycle – from data preparation to model deployment. This can also help reduce the time to value for getting models into production.”

SAS’ evaluation is based on two solutions key to the success of its data scientist users – SAS® Visual Data Mining and Machine Learning and SAS® Enterprise Miner™. Both offer users the ability to solve complex analytical problems that drive better, more rapid decision making.

Running on the SAS® Viya® engine, SAS Visual Data Mining and Machine Learning includes the latest statistical, machine learning, deep learning and text analysis algorithms that accelerate structured and unstructured data explorations, while also supporting popular open source languages. It unifies the entire machine learning process, from data access/transformation and preparation to scoring and deploying, in one environment. SAS Visual Data Mining and Machine Learning “received excellent scores for user interface and data exploration and visualisation. It also received strong scores for data preparation and automation and augmentation,” adds the report.

Valuable across any industry, SAS Enterprise Miner works on any platform and with any data type to identify relationships and patterns buried in a company’s data. It streamlines the data mining process to create accurate predictive and descriptive analytical models to find the best fit, no matter the size of the data set. The Gartner report defines a data science platform as “A cohesive software application that offers a mixture of basic building blocks essential for creating all kinds of data science solution, and for incorporating those solutions into business processes, surrounding infrastructure and products.”

Read more about SAS customers that are benefitting from machine learning.

Gartner, Magic Quadrant for Data Science and Machine Learning Platforms, Carlie Idoine, Peter Krensky, Erick Brethenoux, Alexander Linden, 28 January 2019.The report was previously titled the Magic Quadrant for Data Science Platforms and the Magic Quadrant for Advanced Analytics Platforms.

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