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Oracle unveils Intelligent Data Lake to boost data management

Wed, 11th Sep 2024

Oracle has announced its plans to introduce Oracle Intelligent Data Lake as a new feature of the Oracle Data Intelligence Platform. This addition aims to simplify the use of data from diverse sources through a unified experience, incorporating elements such as orchestration, data warehouses, analytics, and AI within the Oracle Data Intelligence Platform, which operates on Oracle Cloud Infrastructure (OCI).

Oracle Intelligent Data Lake is anticipated to be available in limited release by 2025. The new service will feature an open data lake with a unified developer experience, including a data catalogue capability, Apache Spark and Apache Flink for data processing, and a Jupyter Notebook for data analysis and visualisation. By integrating these services, customers will be able to construct a data lake, link and expand analytical applications with real-time data, inventory assets, transform data, and create end-to-end data orchestration with unified governance and security.

According to Oracle, these capabilities will allow organisations to eliminate data silos, secure data with fine-grained, role-based access control policies, and enhance the accuracy of analytical applications to improve decision-making. For customers of Oracle Data Intelligence applications, Intelligent Data Lake will provide zero-copy integration, allowing for seamless sharing of the catalogue and data across all of Oracle's Data Intelligence Apps.

T.K. Anand, Oracle Analytics Executive Vice President, stated, "With the addition of Oracle Intelligent Data Lake to Oracle Data Intelligence Platform, we're delivering an all-in-one solution that will enable organisations to integrate and analyse 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."

Oracle Data Intelligence Platform is designed to integrate and analyse data from a variety of sources seamlessly. For instance, a global retail company could unify structured data such as sales transactions and inventory levels with unstructured data, including customer reviews, social media sentiment, and images from in-store cameras, within the Oracle Intelligent Data Lake. Retailers could then utilise Oracle Analytics Cloud to create new retail analytics dashboards with the assistance of AI, helping to identify emerging seasonal trends, understand store foot traffic, optimise stock levels in real-time, and personalise marketing campaigns. This unified platform is crafted to be secure, scalable, and user-friendly, aimed at enhancing operations, accelerating insights, and enabling users to make informed business decisions.

Key features of the Oracle Data Intelligence Platform include generative AI-powered experiences that will allow organisations to streamline workflows and enhance productivity by simplifying code generation to deliver conversational analytics and support dashboard creation with minimal technical expertise. Additionally, improved data integration capabilities will help data professionals combine all first and third-party data, whether structured or unstructured, reducing the manual tasks involved in cleaning, governing, and securing data. This enhancement is expected to boost productivity, efficiency, and lower operational costs. Native integrations with Oracle portfolios and open-source standards will enable users to benefit from new insights based on raw, detailed, or third-party data stored in Oracle Intelligent Data Lake.

Oracle has also introduced the Oracle Analytics Cloud AI Assistant, which translates natural language requests into actions. The AI Assistant, which features a built-in large language model (LLM) optimised for analytics tasks, aims to bridge the gap between an analyst's vision and its implementation. Customers have the option to use their own LLM for a more flexible experience. This feature aims to streamline workflows and boost productivity by allowing analysts to focus on deriving insights from data, rather than mastering the tools.

In conjunction with these announcements, Oracle revealed new innovations in its Autonomous Database, including Select AI with RAG support, GPU support for OML Notebooks offload, and new no-code "drag and drop" tools within Data Studio.

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