SAS is reported to be planning to invest $1Billion in AI over the next three years as it continues to develop its analytics platform, target industry-based use cases and educate data scientists.
The investment is said to be part of the company’s recent endeavor to create a higher profile.
Despite being a pioneer in data science and analytics, SAS has been silently retooling both its products and business.
The company’s AI investment will concentrate on services, education projects like its data science academy and certifications, and artificial intelligence (AI) research and development to create higher returns on initiatives.
SAS’ Chief Technology and Operating Officer Oliver Schabenberger is expected to deliver a keynote speech at the Nvidia GPU Technology Conference to be held this week on Tuesday.
The artificial intelligence efforts made by SAS are anticipated to revolve around the integration of AI into the company’s platform and developing tools designed for risk management, fraud and security, customer analytics, and data management.
In an interview regarding SAS’ plan in December, Schabenberger revealed several important points concerning the company’s intentions and where artificial intelligence comes into play:
In recent years, SAS “hasn’t been as visible as it could have been,” claimed Schabenberger.
Nevertheless, the company has been exploring software as a service, linking its platform to other numerous tools and targeting industries in a better manner.
For some time, SAS has been focusing on “how our offering can bring analytics to areas undiscovered.”
Schabenberger also said that the company has been focusing on targeting a variety of companies, especially beyond big enterprises, and making its service more consumable.
SAS is keying in results in a service model where clients can come with business issues and, in turn, the company can help in solving them using its expertise in data science, machine learning, and analytics.
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Many of SAS’ clients are on-premises but are moving to cloud workloads at their own paces, claimed Schabenberger.
While the migration goes on, SAS intends to bridge the existing gap between those who consume the data and those involved in its preparation and programming. “Data needs to be consumed,” said Schabenberger. “Our offering today is more than what SAS became known for.”
The value from the company comes from its expertise in building machine learning algorithms and models.”Our strength is embedding algorithms and bringing them into action to process data into a user model and solution,” said Schabenberger.