Oracle has announced the launch of the Oracle Intelligent Data Lake, slated for limited release by 2025. Integrated with the Oracle Data Intelligence Platform, this new addition intends to streamline data management from diverse sources, enhancing user experience with elements such as orchestration, data warehouses, and AI capabilities within Oracle Cloud Infrastructure (OCI).
The service will offer an open data lake and a unified developer experience. Features include a data catalogue, Apache Spark, Apache Flink for data processing, and Jupyter Notebook for data analysis and visualisation. This combination aims to help users construct data lakes, link analytical applications with real-time data, inventory assets, transform data, and establish end-to-end data orchestration with unified governance and security.
Oracle claims these enhancements will eliminate data silos, providing organizations with fine-grained, role-based access control for secure data management. Additionally, the zero-copy integration feature will allow seamless sharing of catalogues and data across all Oracle Data Intelligence Applications.
T.K. Anand, Oracle Analytics Executive Vice President, noted, “With the addition of Oracle Intelligent Data Lake to Oracle Data Intelligence Platform, we’re delivering an all-in-one solution that will enable organizations to integrate and analyze structured and unstructured data for a more complete view of their business. This will help customers simplify data management, eliminate multiple point solutions, and take advantage of the latest AI innovations and advanced analytics capabilities to drive their business forward.”
The Oracle Data Intelligence Platform aims to integrate and analyze data seamlessly from various sources. For example, a global retail company can unify structured data such as sales transactions with unstructured data like customer reviews and social media sentiment. Utilizing Oracle Analytics Cloud, the retailer can create new dashboards to identify trends, understand store traffic, optimize stock levels, and personalize marketing campaigns. The platform is designed to be secure, scalable, and user-friendly, enhancing operational efficiency and enabling informed business decisions.
Other key features include generative AI-powered experiences that simplify code generation and support conversational analytics and dashboard creation with minimal technical expertise. Enhanced data integration capabilities will make it easier for data professionals to merge structured and unstructured data, reducing manual tasks related to data cleaning, governance, and security. These improvements are expected to boost productivity and lower operational costs.
Additionally, native integrations with Oracle portfolios and open-source standards help users derive new insights from raw, detailed, or third-party data stored in the Oracle Intelligent Data Lake.
A notable innovation is the Oracle Analytics Cloud AI Assistant, which interprets natural language requests into actionable insights. This feature uses a built-in large language model (LLM) optimized for analytics tasks. Customers can also use their own LLM for a more personalized experience, which simplifies workflows and boosts productivity by allowing analysts to focus on deriving insights rather than managing tools.
