Abstract: Many users, organizations, and enterprises rely on R as a powerful language and environment for statistical analysis, data science, and machine learning. Many of these same users work with data in - or extracted from - Oracle databases. As data volumes increase, moving data complicates the life of data professionals, like data engineers and data scientists, as well as solution developers and administrators. In this session, you'll learn how to increase overall solution performance with R tightly integrated with Oracle databases. Oracle Machine Learning for R (OML4R) leverages the database as a high-performance computing environment, enabling users to explore, transform, and analyze data faster and at scale, while allowing the use of familiar R syntax and semantics. In-database parallelized machine learning algorithms are exposed through a natural R interface, including the use of R Formula. R users can run user-defined R functions in database-environment spawned and managed R engines using R, SQL, and REST interfaces - even taking advantage of system-enabled data parallelism. User-defined R functions and other R objects can be stored directly in the database to facilitate ease of solution deployment while benefiting from database security – avoiding the use of flat files. Join us for this engaging session highlighting multiple use cases with demonstrations.