The challenge of finding value from data is becoming ever-harder for many organisations, with SAS looking to overcome these challenges by enhancing its analytics offering with AI.
Adding such capabilities like image recognition, deep learning and natural language understanding to the SAS Platform, the analytics giant aims to help organisations foster grater collaboration and drive innovation via data-driven insights.
New enhancements to the SAS Platform on the AI front include SAS Visual Data Mining and Machine Learning and SAS Visual Text Analytics. Building on a long history of machine learning, these products provide deep learning and natural language understanding to enhance the depth of insights derived from data.
The company has also introduced SAS Visual Text Analytics, a modern, flexible and end-to-end text analytics framework that combines text mining, contextual extraction, categorisation, sentiment analysis and search. It automates feature extraction and business-rule generation using modern machine learning approaches. Adding to the new enhancements on the SAS Platform, SAS Visual Analytics for self-service discovery and analytics adds new ways to visualise data relationships, tapping into the power of location analytics and bringing a refined user experience.
SAS has also confirmed cloud deployment through the SAS Cloud, Amazon Web Services, Microsoft Azure and others, including SaasNow, as well as offering a single interactive interface that spans a wide range of analytics tasks and disciplines to help non-coders solve complex problems faster.
“The AI revolution has truly arrived as businesses throughout the world utilise the technology to improve accuracy, boost efficiency and productivity and create new services. Through embracing AI, SAS Viya will continue to provide our customers with the analytics and insight they need to thrive and grow,” said Peter Pugh-Jones, Head of Technology at SAS UK & Ireland.
One company that has already seen the benefits of added AI capabilities is SciSports, a football analyst company in the Netherlands. The company advises and builds solutions to determine the influence of individual players on team results, track player development, determine potential market value for a player, and predict game results.
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Through the SAS and SciSports development partnership, the companies intend to use SAS Viya capabilities and SciSport’s BallJames camera system with the goal of using object detection to access player movements through 3-D images.
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With cameras capturing footage in real time, SAS AI capabilities can model player movements, and that data can then be used to identify rising stars or undervalued players by benchmarking their performance against others in a given league.
“SAS has the potential to give us four key things we need,” said Wouter Roosenburg, Chief Technology Officer at SciSports.
“The ability to scale our processing power up or down as needed; the option to put models into production in real time using SAS Event Stream Processing; the ease of development and discovery in one platform; and the flexibility to call Python or other open source software.”
