The integration of generative Artificial Intelligence (AI) solutions has become increasingly important for companies looking to improve data management and streamline processes. To help companies achieve this goal, SAS has announced an alliance with Microsoft to advance the integration of these solutions on its SAS Viya advanced analytics platform. This strategic partnership is a valuable opportunity to explore the next frontier in data management: generative AI.
According to a comparative study published by The Futurum Group, the SAS Viya platform is faster and more cost-effective compared to commercial and open-source alternatives, making it a popular choice for data management across various sectors. SAS continues to look for ways to increase the speed, scalability, and efficiency of its platform, offering functions such as bias detection, model monitoring, governance, or accountability to demonstrate responsible AI practices.
To further support responsible innovation, SAS has also launched internal training programs where its employees can learn how to use its software effectively and ensure that analysts are using correct data processing techniques. The use of data and statistics has been integrated almost transversally into sports, where AI and machine learning technologies can find patterns and trends that coaches can use to devise better strategies for their teams. For example, the French Rugby team has only lost four of their last thirty official matches thanks to these technological advancements.
SAS’s partnership with Microsoft can help companies achieve greater decision speed by leveraging capabilities like synthetic data, digital twin simulation, and large language models. By integrating these tools into their existing systems, companies can gain valuable insights from their data more quickly and efficiently than ever before. Overall, this strategic alliance represents a significant opportunity for companies looking to stay ahead in the race to digitize and optimize their operations through effective data management practices.