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Oracle Helps Utilities Transform Raw Data into Intelligence

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Oracle (ORCL) has unveiled its new Oracle Energy and Water Data Exchange, a cloud-based solution aimed at transforming utility data management and AI implementation. The platform standardizes fragmented enterprise and third-party information into a unified industry model with natural language meaning.

Built on Oracle Cloud Infrastructure (OCI), the solution features validation checks, error reporting, cleansing, and synchronization processes to ensure data accuracy. It incorporates multiple industry standards including IEEE and IEC, facilitating secure data sharing across partners. The platform leverages OCI Integration Services and Oracle Database 23ai's AI Vector Search and machine learning capabilities.

The solution specifically targets IT teams, consultants, and integration specialists, focusing on managing data quality across sources and enabling smooth integration between disparate systems. Oracle plans to expand the platform to include a data sharing framework for validated data exchange across teams and external partners.

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Positive

  • New cloud solution addresses critical data management needs in utilities sector
  • Integration with Oracle Database 23ai provides advanced AI and ML capabilities
  • Platform enables faster implementation of AI and analytics projects
  • Solution can standardize data from multiple sources including government agencies

Negative

  • None.

News Market Reaction 1 Alert

-2.43% News Effect

On the day this news was published, ORCL declined 2.43%, reflecting a moderate negative market reaction.

Data tracked by StockTitan Argus on the day of publication.

Oracle Energy and Water Data Exchange standardizes disparate information into logical formats to help speed advanced AI use cases and data sharing

NASHVILLE, Tenn., March 3, 2025 /PRNewswire/ -- Oracle Customer Edge Summit -- Oracle today announced Oracle Energy and Water Data Exchange, a new cloud-based solution designed to streamline data integration, sharing, and preparation for AI use cases. Applying an intelligent semantic layer, the offering translates complex raw enterprise and third-party information into a standardized industry model with natural language meaning for easier interpretation and action. This often overlooked, but critical, data preparation step helps ensure that information is not only accessible but also meaningfully contextualized for analytics and AI-driven insights. With the Data Exchange, cloud developers, data scientists, and analysts can significantly fast-track priority projects, including data mining, predictive analytics, and cutting-edge generative AI (GenAI) applications.

"Utilities are under increasing pressure to accelerate digital transformation, however, many struggle with fragmented, siloed, and inconsistently labeled data spread across multiple sources. This makes it difficult to unify information and use effectively to innovate and improve utility operations," said Hillary Martin, vice president of analytics and innovation, Oracle Infrastructure. "By cleansing, organizing, and adding the appropriate meaning to an organization's data, Oracle Energy and Water Data Exchange makes data easier to find, understand, and leverage for AI and advanced analytics use cases that can transform raw data into actionable insights."

Preparing data for action
Many utilities have invested in industry solutions that promise to centralize and unlock the value of data only to be stifled by inconsistent, hard-to-find, and unstructured data. Unlike other solutions, Oracle Energy and Water Data Exchange addresses these foundational problems by focusing on data quality and meaning. Through a series of validation checks, error reporting, cleansing, deduplication, and synchronization processes, the offering helps ensure that data is accurate, easy-to-understand, and ready for analysis, replication, or AI application use. 

Oracle Energy and Water Data Exchange features an industry data model that unifies multiple standards—including IEEE and IEC—which helps ensure that when data is ready for production, it can be securely shared across partners to streamline integration, enhance interoperability, and drive operational efficiency. With this clean, validated data, utilities can expedite analytics-based decisions and priority use cases, such as connecting Distributed Energy Resources (DERs) to grid and customer devices to provide a comprehensive view of grid conditions across EV charging locations in a specific area.

AI-ready data
Oracle Energy and Water Data Exchange is focused on unifying data from Oracle and other third-party industry applications. It also can standardize and cleanse public data sources such as the U.S. Department of Energy, U.S. Census Bureau, and National Oceanic Atmospheric Administration (NOAA) for further intelligence.

The solution is built on the security, performance, and scalability of Oracle Cloud Infrastructure (OCI) and takes advantage of a number of OCI services. For example, Data Exchange natively synchronizes with OCI Integration Services to connect any application and data source for automated end-to-end processes, centralized management, and simplified migration to the cloud.

Oracle Energy and Water Data Exchange also leverages the built-in AI Vector Search and in-database machine learning capabilities of Oracle Database 23ai to help eliminate the complexity and cost of integrating and managing multiple databases. This helps maintain data consistency across areas such as smart meters, distribution assets, and utility grids. Unique, language-based semantic representations also make it easy to create embeddings for data, feed GenAI engines, and enhance applications such as smart chatbots. 

Oracle Energy and Water Data Exchange is ideal for IT teams, consultants, integration specialists, and solution architects who have been tasked with integrating multiple data sources across an enterprise. The solution makes it easier to manage data quality across sources, enable smooth integration between disparate systems, and address inconsistencies and information misalignments. This helps lead to faster integrations, fewer errors during data migration or system updates, and enhanced solution performance for higher client satisfaction. Oracle plans to expand the solution to include a data sharing framework, enabling secure and efficient sharing of validated data across teams and external partners.

See Oracle Energy and Water Data Exchange in action at Oracle Customer Edge Summit or learn more at Oracle.com/utilities or LinkedIn.

About Oracle
Oracle offers integrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud. For more information about Oracle (NYSE: ORCL), please visit us at www.oracle.com.

Trademarks
Oracle, Java, MySQL and NetSuite are registered trademarks of Oracle Corporation. NetSuite was the first cloud company—ushering in the new era of cloud computing.

Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/oracle-helps-utilities-transform-raw-data-into-intelligence-302389519.html

SOURCE Oracle

FAQ

What are the key features of Oracle's new Energy and Water Data Exchange solution for ORCL?

The solution features data validation, cleansing, deduplication, and synchronization processes, built on OCI with integrated AI Vector Search and machine learning capabilities from Oracle Database 23ai.

How does Oracle's Energy and Water Data Exchange help utilities with AI implementation?

It standardizes raw enterprise and third-party data into a unified industry model with natural language meaning, making it easier to implement data mining, predictive analytics, and generative AI applications.

What industry standards does the new ORCL Energy and Water Data Exchange support?

The solution unifies multiple standards including IEEE and IEC to ensure secure data sharing and enhanced interoperability across partners.

What expansion plans does Oracle have for its Energy and Water Data Exchange platform?

Oracle plans to add a data sharing framework to enable secure and efficient sharing of validated data across teams and external partners.
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