SAS says its new visual data mining and machine learning software, available later this month, will “feed this need for smarter analytics”.
The company was speaking about its new solution at its Analytics Experience conference in Las Vegas attended by more than 10,000, on-site and online, to discuss business issues.
“SAS Data Mining and Machine Learning is built on the company’s solid expertise and reputation of delivering scalable and adaptable analytics that solve real business problems and yield measurable business value,” said Jonathan Wexler, SAS analytics product manager.
“This software helps provide positive outcomes to increase profitability, better understand customer behaviour and decrease the cost of doing business.”
Wexler said advanced analytics offer insight to businesses, but "machine learning and deep learning algorithms take it deeper, insights that were previously out of reach”.
By way of example, SAS says machine learning use can include facial recognition in security systems, speech recognition in customer service applications, accurate product recommendations in e-commerce, self-driving cars and medical diagnostics.
Designed to boost data scientist productivity, SAS says its Visual Data Mining and Machine Learning features include:
• Flexible, Web-based programming;
• Highly scalable, in-memory data manipulation and analytical processing;
• Powerful data manipulation and management;
• Data exploration, variable transformations and dimension reduction;
• Modern statistical, data mining and machine-learning techniques;
• Integrated text analytics;
• Model assessment and scoring; and
• Access to algorithms from Python, Lua, Java.
SAS Visual Data Mining and Machine Learning is one of the initial analytics applications on the SAS Viya platform, and described by SAS as an “innovative analytics environment designed for use in the cloud that provides the power of SAS Analytics through SAS interfaces as well as open APIs for Python, Lua, Java and REST”.
Wexler says the new analytics offerings for SAS Viya are structured for diverse users, while maintaining consistency and manageability.
In addition to SAS Visual Data Mining and Machine Learning for data scientists, the Viya family will include SAS Visual Analytics for business analysts and SAS Visual Statistics, which SAS says are aimed at experienced statistical users.
“The breadth of SAS Viya applications will satisfy the appetites of all user types, while maintaining a consistent structure. The speed of the multithreaded parallel processing engine in SAS Viya will drive faster decisions. And the strength of analytics from the advanced analytics leader will produce trusted results,” Wexler says.
The latest SAS additions to the portfolio of analytics that contribute to cognitive computing are SAS Visual Data Mining and Machine Learning and SAS Visual Investigator.
“Cognitive computing is disruptive, combining technologies such as natural language processing, image processing, text mining and machine learning to augment human intelligence,” said Oliver Schabenberger, SAS executive vice-president and chief technology officer.
“SAS has supported cognitive technologies in analytics for decades. The exciting change is applying deep learning and high-performance computing to achieve greater automation and accuracy in the interaction between computers and people.
“SAS has had cognitive elements for some time, based on proven technologies like our text-mining and machine-learning software. And we will continue to develop cognitive approaches and applications that help our customers take advantage of this exciting and evolving area.”
Cognitive capabilities based on deep learning and artificial intelligence will be embedded in SAS solutions built on the SAS Viya platform, with cognitive services including question-answer systems that drive analytics, make recommendations, or learn from user responses.
SAS says customers will also have access to cognitive analytics, image processing, and deep learning in the open Viya platform, enabling them to build cognitive solutions.