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The Oracle Cloud Data Science Platform has seven new services, with Oracle Cloud Infrastructure Data Science at the core. Oracle Cloud Infrastructure Data Science is designed to help enterprises build, train, manage, and deploy machine learning models to increase the collaborative success of data science projects. Today most organizations realize only a fraction of the transformational potential of data as a result of access, tools to build, and ability to deploy effective machine learning models.
“Success of this vision relies on the ability to manage a continuous and increasing flow of input data and our own AI-based solution to transform that data into precision and decision agriculture, at scale. The speed, scale, and agility of Oracle Cloud have helped us realize our dream. Now, new horizons have opened up with the recent addition of Oracle Cloud Infrastructure Data Science that improves our data scientists’ ability to collaboratively build, train, and deploy machine learning models.”
Simcha Shore, Founder and CEO, AgroScout
Oracle Cloud Data Science Platform includes seven new services that deliver a comprehensive, end-to-end experience that accelerates and improves business decisions.
Enables users to build, train, and manage new machine learning models on Oracle Cloud using Python and other open-source tools and libraries, including TensorFlow, Keras, and Jupyter.
Provides powerful new machine learning capabilities tightly integrated in Oracle Autonomous Database, with new support for Python. Upcoming integration with Oracle Cloud Infrastructure Data Science will enable data scientists to develop models using both open source and scalable in-database algorithms. Uniquely, bringing algorithms to the data in Oracle Database speeds time to results by reducing data preparation and movement.
Allows users to discover, find, organize, enrich, and trace data assets on Oracle Cloud. Oracle Cloud Infrastructure Data Catalog’s built-in business glossary makes it easy to curate and discover the right, trusted data.
Offers a full Cloudera Hadoop implementation with dramatically simpler management than other Hadoop offerings, including just one click to make a cluster highly available and to implement security. Oracle Big Data Service also includes machine learning for Spark, allowing organizations to run Spark machine learning in memory with one product and with minimal data movement.
Enables SQL queries on data in HDFS, Hive, Kafka, NoSQL, and Object Storage. Only Cloud SQL enables any user, application, or analytics tool that can talk to Oracle databases to transparently work with data in other data stores, and offers the benefit of push-down, scale-out processing to minimize data movement.
A fully managed big data service that allows users to run Apache Spark applications with no infrastructure to deploy or manage, enabling enterprises to deliver big data and AI applications faster. Unlike competing Hadoop and Spark services, Oracle Cloud Infrastructure Data Flow includes a single window to track all Spark jobs, making it simple to identify expensive tasks or troubleshoot problems.
Preconfigured, GPU-based environments with common IDEs, notebooks and frameworks that can be up and running in under 15 minutes, for US$30 a day.
Machine learning is a key component in a big data world, helping data scientists organize, build, train, and deploy data models.
Supporting tools and features expand the possibilities of data science by optimizing performance, scalability, and efficiency.