For most organizations today, managing the analytics lifecycle is largely a manual process. Moving data and models from creation to production often involves tedious programming or operating system translations as analyzes are sent across platforms. Model decay is another serious challenge. Retaining poorly performing models can result in inaccurate projections, which lead to poor business decisions. The lack of a common framework for managing an analytics model throughout its lifecycle is also painfully evident as organizations struggle to meet the deadlines required by internal processes. In this presentation, we'll show you how SAS Viya solves these issues, enabling all stakeholders to collaborate while managing the analytical modeling workflow efficiently and cost-effectively, and also streamlining the entire modeling process to generate consistent and timely results.