Enterprises are embarking on analytics journeys across regions and domains as part of their digital transformation and evolution. They are faced with scalability, automation and governance challenges; a variety of execution targets; complex interfaces; and the lack of a unified platform. This impacts productivity and creates a gap between data engineers, data scientists, IT and business. As a result, companies are not getting full value from their investments in analytics. In the analytics life cycle, value means making confident, informed decisions in the moments that matter using AI-driven insights. With 42% of data scientists reporting their models don't get used by decision makers, it seems organizations can envision their victory, which translates to increased operations efficiency, customer loyalty, higher market standings, achieving compliance, reduced risk and fraud, and quicker responses in high agility environments, but they can't yet attain it. SAS Intelligent Decisioning (SID) is a leader in AI decisioning platforms and helps enterprises achieve value through operationalizing models seamlessly and at scale, offering a low-code, intuitive interface that boosts productivity and bridges the gap between all analytics and decision makers. This session will give an overview of SID and how to get started, and show examples of capabilities that counteract challenges across the analytics life cycle.
