Story image

SAS a machine learning Leader in 2019 Magic Quadrant

04 Feb 2019

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 and, for the sixth consecutive year, gave them the rank of Leader in this Magic Quadrant.

“Machine learning is a critical tool in the modern data scientist toolbox,” says SAS artificial intelligence and machine learning strategist Lorry Hardt. 

“It allows organisations to quickly identify opportunities for their business, but also avoid risks that may go unnoticed by humans.”

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.”

Venafi and nCipher Security partner on machine identity protection
Cryptographic keys serve as machine identities and are the foundation of enterprise information technology systems.
Why Aussie companies are struggling with data
The top culprits in poor data quality in Oz are human error, different data sources, lack of comms, inadequate strategy, and too much information.
Machine learning is a tool and the bad guys are using it
KPMG NZ’s CIO and ESET’s CTO spoke at a recent cybersecurity conference about how machine learning and data analytics are not to be feared, but used.
Pure Storage expands enterprise data management solutions
It has integrated StorReduce technologies for a cloud-native back up platform, and expanded its data fabric solution for cloud-based applications.
Survey finds DC managers want more efficiency, not horsepower
More servers and more CPU power used to be the answer to boosting data centre performance, but it appears this is no longer the case.
GoCardless to double A/NZ team by end of year
With a successful E round of investment and continuing organic growth globally, the debit network platform company aims to expand its local presence.
Micro Focus acquires Interset to improve predictive analytics
Interset utilises user and entity behavioural analytics (UEBA) and machine learning to give security professionals what they need to execute threat detection analysis.
TechOne bringing solar lights to students in need
The company is partnering with charity SolarBuddy to bring solar-powered lights to children in energy poverty to alleviate study stress after dark.