Oracle Intelligent Data Lake will include open data formats, a unified catalog, and modern developer experiences to build rich data intelligence solutions
Intelligent Data Lake is designed to include an open data lake with a unified developer experience, including a data catalog capability, Apache Spark and Apache Flink for data processing, and a Jupyter Notebook for data analysis and visualization. With these combined services, customers will be able to build a data lake, connect and extend analytical applications with real-time data from any source, inventory assets, transform data, and create end-to-end data orchestration, with unified governance and security. This will help customers ensure data is secure with role-based access control policies and eliminate data silos and enable analytical applications to provide more accurate answers for better decision making. Additionally, for Oracle Data Intelligence applications customers, Intelligent Data Lake will offer zero-copy integration with seamless sharing of catalog and data across all Oracle Data Intelligence applications.
“With the addition of Oracle Intelligent Data Lake to Oracle Data Intelligence Platform, we are delivering an all-in-one solution that will enable companies to integrate and analyze structured and unstructured data to gain a more comprehensive view of their business,” said TK Anand, executive vice president, Oracle Analytics. “This will help customers simplify data management, eliminate multi-point solutions, and leverage the latest AI innovations and advanced analytics capabilities to drive their business forward.”
Oracle Data Intelligence Platform enables businesses to seamlessly integrate and analyze data from diverse sources. For example, a global retail company can unify structured data, such as sales transactions and inventory levels, with unstructured data, including customer reviews, social media sentiment, and in-store camera footage, in Oracle Intelligent Data Lake. A retailer can then use Oracle Analytics Cloud to quickly create new AI-powered retail analytics dashboards to uncover emerging seasonal trends, understand in-store traffic, optimize inventory levels in real time, and personalize marketing campaigns. All of this will happen within a secure, scalable, and easy-to-use platform designed to improve operations, accelerate insights, and empower users to make better business decisions.
Key features of the Oracle Data Intelligence platform will include:
- AI-powered generative experiences: Will enable organizations to leverage powerful generative AI-powered capabilities to streamline workflows and improve productivity by simplifying code generation to deliver conversational analytics and facilitate dashboard creation with minimal technical expertise.
- Improved data integration: Will enable data professionals to combine all internal and external data, whether structured or unstructured, to reduce the administrative burden of cleaning, governing and securing data. This will help customers increase productivity and operational efficiency, manage large-scale data workloads and reduce costs.
- Native integrations with Oracle wallets and open source standards: Users will benefit from native integrations with Oracle’s data, analytics, and AI portfolios, including Oracle Autonomous Data Warehouse and Oracle Analytics Cloud, as well as open source standards such as Kafka, Delta Lake, Iceberg, and Parquet. This will enable organizations to gain new insights based on raw, detailed, or third-party data stored in Oracle Intelligent Data Lake.
Oracle Analytics Cloud AI Assistant
Oracle also announced the availability of Oracle Analytics Cloud AI Assistant, which translates natural language into action. It bridges the gap between an analyst’s vision and its realization on the canvas. Analytics Cloud AI Assistant understands the context of a user’s question because it has a built-in LLM optimized for conversations and analytics tasks that recognize the Oracle Analytics workbook and datasets. Optionally, customers can bring their own LLM for a flexible user experience. Analytics Cloud AI Assistant streamlines workflows and improves productivity, allowing analysts to focus on data insights instead of mastering tools.
Oracle Autonomous Database Innovations
Oracle also unveiled new innovations for Autonomous Database, including Select AI with RAG support, GPU support for OML notebook offloading, and new no-code drag-and-drop tools within Data Studio.
Additional Resources
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The above information is intended to describe the general direction of our products. It is provided for informational purposes only and may not be incorporated into any contract. It does not constitute a commitment to deliver any hardware, code, or functionality and should not be relied upon to make purchasing decisions. The development, release, timing, and pricing of any feature or functionality described for Oracle products are subject to change and remain at the sole discretion of Oracle Corporation.
Disclaimer Regarding Forward-Looking Statements
Statements in this article regarding Oracle’s future plans, expectations, beliefs and intentions are “forward-looking statements” and are subject to significant risks and uncertainties. Many factors could affect Oracle’s current expectations and actual results, and could cause actual results to differ materially. A discussion of these factors and other risks that affect Oracle’s business is contained in Oracle’s filings with the Securities and Exchange Commission (SEC), including Oracle’s most recent reports on Forms 10-K and 10-Q under the caption “Risk Factors.” These filings are available on the SEC’s website or on Oracle’s website at oracle.com/investorAll information in this article is current as of September 10, 2024, and Oracle assumes no obligation to update any statements in light of new information or future events.
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SOURCE Oracle
