Denodo announced the launch of Denodo Platform 9.2, adding new intuitive functionality to Denodo Platform 9.1, released in November, 2024, that builds on the Denodo Platform's semantic layer and logical data management capabilities: a full-featured data marketplace, extended support for GenAI initiatives, and a new suite of self-service tools for the development of data products.

"By continuously evolving our capabilities in the areas of data-self service, data product development, and GenAI, Denodo is enabling enterprises to leverage data more effectively to enhance decision-making, automate complex workflows, and deliver more powerful services," said Alberto Pan, chief technology officer at Denodo. "These innovations will put organizations at the forefront of data-driven transformation, maximizing the impact of their data investments."

A Powerful Data Marketplace to Streamline Data Usage

Business users continue to struggle to access the data they need in an actionable format. The new data marketplace features of Denodo Platform 9.2 offer an e-commerce-style user experience, supported by a comprehensive semantic layer for the most relevant business context, as well as by AI-powered automation, to streamline repetitive tasks. With this new functionality, people with different roles throughout an organization can more quickly and intuitively explore, discover, and access data, with extended visibility into usage beyond the data layer. The data marketplace provides a view into how downstream applications and analytical tools use data, and which data products are being consumed by which dashboards and reports. It also enables individual users to select their preferred language for the UI, which is ideal for global teams. 

"The Denodo Data Catalog has always made data easier to access and use, even across organizations data lakehouse and supporting data sources," said Stewart Bond, research vice president at IDC, "but I believe the new data marketplace functionality of Denodo Platform 9.2 makes access even more intuitive with a more user-friendly interface. Now, people with less or no technical knowledge of data catalogs can leverage the marketplace for data access with little or no guidance."

Enhanced Support for Generative AI (GenAI) Applications

Generative AI (GenAI) applications require immediate access to trusted data from across the organization. Denodo Platform 9.2's GenAI features extend the capabilities of Denodo Platform 9.1, which brought the AI-powered Denodo Assistant and Denodo AI SDK, to streamline the development of GenAI applications.

Denodo Platform 9.2 continues to advance data management capabilities that accelerate the adoption of GenAI, so organizations can seamlessly provide AI models with AI-ready data - high-quality, well-governed data, delivered in real time. These new GenAI advancements include the ability to dynamically customize AI models with user-specific knowledge; enhanced support for unstructured data, to more effectively extract sentiment from social media posts or analyze images; and a new certification program specifically designed for GenAI developers.

"With Denodo Assistant and its AI SDK, we've dramatically expanded access to governed data across Alexforbes," said Barend Van Coller, Data Analyst and Data Governance team lead at Alexforbes. "What was once the domain of IT and power users is now accessible to non-technical users through intuitive, conversational interactions. We're excited about the upcoming Denodo 9.2 release, which further empowers our teams to search, discover, and interact with data - securely and seamlessly."

Streamlined Development of Data Products

Developers need to be able to build data products in a controlled, organized environment, and Denodo Platform 9.2 includes significant enhancements to facilitate data product development while maintaining strong data governance and optimal efficiency. These new additions include workspace support for continuous integration/continuous development (CI/CD), enabling branch-based development for more agile collaboration across multiple teams; automated dependency analysis, to reduce errors and streamline data caching and curation; and expanded support for open table formats, to improve support for Databricks Unity Catalog, Snowflake's Open Catalog, and other solutions across the open table ecosystem.