Businesses have rapidly increased their adoption of AI over the past year. Gartner forecasts that by 2026, over 80% of enterprises will have implemented AI APIs or generative AI applications in production environments, a significant rise from less than 5% in 2023. However, leveraging AI effectively depends on the quality and availability of the underlying data. To fully capitalize on data for AI, enterprises need to navigate complex IT landscapes, facilitate data access, optimize workload performance at scale, and ensure governance.
IBMwatsonx.dataempowers enterprises to scale AI and analytics by integrating with their existing data, no matter where it is stored. As a key component of the IBM watsonx AI and data platform, it supports the creation of tailored AI applications, efficient data management, and the acceleration of responsible AI workflows, all within a single platform.
watsonx.dataconnects to current storage and analytical environments, enabling businesses to unlock value from their existing data, prepare it for AI applications, and optimize costs with various query engines and cost-effective object storage.
Accelerate data discovery and insights with a semantic layer–no SQL required
Excited to announce the upcoming launch of the semantic layer, a new feature in IBM Knowledge Catalog that will also be integrable intoIBM watsonx.data. This semantic layer leverages large language models (LLMs) to create a unified data context across IBM Data and AI tools. Powered by watsonx, it not only enhances data but also offers automation tools to help teams swiftly explore and process information.
When integrated with IBM watsonx.data, the semantic layer will provide data enrichments that allow clients to interpret and navigate complex, structured data using natural language through semantic search. This innovation will accelerate data discovery and unlock insights more quickly—no SQL knowledge required.
A notable example of ALM in action is Transport for London (TfL), which is optimizing public transportation assets such as buses, boats, bikes, and the tube. IBM’s technology aids TfL in preemptively addressing issues and extending asset lifecycles, thereby reducing the need for replacements and mitigating the risk of major failures. TfL estimates a net savings of GBP 21 million over the next decade solely for its London Underground operations.
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