Oracle Adds New Data Science Services to Cloud Platform
The new suite enables data analysis and machine learning workflows on existing customer data without the need for migration.
Updated on Oct. 28, 2026 in Data Centers
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On February 12, 2026, Oracle expanded its cloud infrastructure platform with new data science, catalog, and query services. These tools allow existing database customers to run machine learning and big data analytics without migrating their data off the platform.
Why it matters
These services provide a pathway for enterprises to modernize data workflows and launch machine learning initiatives within their existing infrastructure environments. By enabling in-place analysis, the company aims to reduce the technical friction associated with data migration.
The Data Flow service enables Apache Spark processing by allowing users to upload scripts and specify compute resources based on defined CPU requirements. The new catalog service automates data management by introspecting warehouse models to track ownership, usage, and data availability.
The players
Oracle
A global technology company providing cloud infrastructure, database management systems, and enterprise software.
The details
The newly announced Oracle Cloud Infrastructure Data Science offering provides an automated workflow to streamline machine learning and data analysis tasks. To maintain data integrity and visibility, the integrated data catalog service automatically scans existing data warehouse models. Meanwhile, the Cloud SQL service enables users to execute standard database queries directly against cloud-based storage, and the Data Flow service facilitates Apache Spark—an open-source unified analytics engine for large-scale data processing—executions.
Timeline
Oracle acquired DataScience.com in 2018.
Oracle unveiled the new data services on February 12, 2026.
The Tech Race
The release marks a step in the competition to provide unified data science and processing environments within major cloud platforms. It follows the strategy initiated by the 2018 acquisition of DataScience.com to embed advanced analytics directly into the cloud platform.
Database customers can now incorporate data science projects into their existing workflows without the cost and complexity of moving data to separate environments. Oracle has also signaled a future release of a data integration service to handle additional ETL and data preparation tasks.
The takeaway
These services offer a practical path for teams to leverage existing database assets for modern machine learning and big data tasks. Watch for the forthcoming release of the company's data integration service to complete the currently announced pipeline of tools.
Further reading
Learn more about evolving infrastructure requirements at Data Centers.
Source note: This article includes information reported by TechTarget.
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