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Redwood Shores Calif—12 February 2020
Oracle today announced the availability of the Oracle Cloud Data Science Platform. At the core is Oracle Cloud Infrastructure Data Science, helping enterprises to collaboratively build, train, manage and deploy machine learning models to increase the success of data science projects. Unlike other data science products that focus on individual data scientists, Oracle Cloud Infrastructure Data Science helps improve the effectiveness of data science teams with capabilities like shared projects, model catalogs, team security policies, reproducibility and auditability. Oracle Cloud Infrastructure Data Science automatically selects the most optimal training datasets through AutoML algorithm selection and tuning, model evaluation and model explanation.
Today, organizations realize only a fraction of the enormous transformational potential of data because data science teams don’t have easy access to the right data and tools to build and deploy effective machine learning models. The net result is that models take too long to develop, don’t always meet enterprise requirements for accuracy and robustness and too frequently never make it into production.
“Effective machine learning models are the foundation of successful data science projects, but the volume and variety of data facing enterprises can stall these initiatives before they ever get off the ground,” said Greg Pavlik, senior vice president product development, Oracle Data and AI Services. “With Oracle Cloud Infrastructure Data Science, we’re improving the productivity of individual data scientists by automating their entire workflow and adding strong team support for collaboration to help ensure that data science projects deliver real value to businesses.”
Oracle Cloud Infrastructure Data Science includes automated data science workflow, saving time and reducing errors with the following capabilities:
Getting effective machine learning models successfully into production needs more than just dedicated individuals. It requires teams of data scientists working together collaboratively. Oracle Cloud Infrastructure Data Science delivers powerful team capabilities including:
With Oracle Cloud Infrastructure Data Science, organizations can accelerate successful model deployment and produce enterprise-grade results and performance for predictive analytics to drive positive business outcomes.
The Oracle Cloud Data Science Platform includes seven new services that deliver a comprehensive end-to-end experience designed to accelerate and improve data science results:
AgroScout is dedicated to detecting early stage crop diseases to improve crop yields, reduce pesticide use and increase profits. “Our vision is to make modern agronomy economically accessible to the 1 billion farmers working on 500 million farms worldwide, constituting 30 percent of the global workforce. We plan to achieve this by offering cloud based, AI-driven sustainable agronomy, relying purely on input from low cost drones, mobile phones and manual inputs by growers,” said Simcha Shore, Founder and CEO AgroScout. “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. Speed, scale and agility of Oracle Cloud has 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. This addition has reduced costs, increased efficiency and has helped us increase our global footprint faster.”
IDenTV provides advanced video analytics based on AI capabilities powered by computer vision, automated speech recognition and textual semantic classifiers. “With Oracle Cloud Infrastructure Data Science, we are able to scale our data science efforts to deliver business value faster than ever before. Our data science teams can now seamlessly access data without worrying about the complexities of data locations or access mechanisms. While using open-source capabilities like TensorFlow, Keras, and Jupyter notebooks embedded within the environment, we can streamline our model training and deployment tasks resulting in tremendous cost savings and faster results,” said Amro Shihadah, Founder and COO, IDenTV. “We feel that Oracle Cloud Infrastructure Data Science in conjunction with benefits of Autonomous Database will give us the edge we need to be competitive and unique in the market.”
The Oracle Cloud offers a complete suite of integrated applications for Sales, Service, Marketing, Human Resources, Finance, Supply Chain and Manufacturing, plus Highly Automated and Secure Generation 2 Infrastructure featuring the Oracle Autonomous Database. For more information about Oracle (NYSE: ORCL), please visit us at www.oracle.com/uk.
The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation.
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