Analytics and Data Summit 2019

Most machine learning projects fail to go beyond the data scientist. They hit a wall when they try to “operationalize” the ML models into enterprise production IT environments. Open source Python and R are great for data scientists but create problems with the DBA. This dichotomy between IT and data science is eliminated when the ML algorithms are part of the enterprise data management platform. By “moving algorithms to the data”, Oracle has extended the Oracle Database, Autonomous Database and Big Data platforms into hybrid data management and machine learning platforms. Data scientists and application developers can use their language or UI of choice (R, Python, SQL, “drag and drop” UIs and notebooks) to cooperatively build, develop and deploy ML models on premise or in the cloud. Learn how data scientists move beyond “ML tools” and now collaborate with IT, DBAs and application developers to deliver ML enabled applications. Several “Predictive Applications” will be shown.