One of the oxymorons regarding the fast-changing technology landscape is that the more time-saving and performance-boosting technologies a company onboards, the more complex and time-consuming it becomes to manage. The key to navigating the complexities of managing the many layers of the enterprise data stack in the AI Era is interoperability.
With this goal in mind, IBM has launched two new software products, IBM watsonx.data integration and IBM watsonx.data intelligence to unify, govern, and operationalize unstructured data for AI use cases.
Operationalizing Unstructured Data
“Businesses need generative AI — and increasingly, agentic AI — to drive innovation, unlock productivity, and remain competitive. And generative AI needs enterprise-specific data to be accurate and performant,” said Ritika Gunnar, General Manager, Data and AI, IBM, in a blog post.
Gunnar explains that a significant portion of enterprise data is unstructured, and the established retrieval augmented generation (RAG) technique struggles to handle the scale and diversity of this data. However, testing with watsonx.data has shown that IBM’s new products can produce AI results that are 40% more accurate than those generated by RAG.
Emphasizing the adaptability of the new software, Gunnar states, “The new software is hybrid and open, connecting with third-party data stacks to provide flexibility, interoperability, and drive innovation from across the ecosystem.”
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In terms of capabilities, watsonx.data integration is a unified data integration “control plane.” This control plane acts as a central hub, providing data engineers with the tools to scale the accessibility of AI-ready data. The new software enables data teams to integrate data, structured and unstructured, from diverse sources with functionality in place that ultimately future-proofs these capabilities in anticipation of emerging data storage trends.
watsonx.data intelligence uses AI to simplify and enhance data curation, management, and operationalization, integrating governance, quality, and lineage functions, and data sharing capabilities.
“Select capabilities from both products will also be available through watsonx.data, IBM’s hybrid, open data lakehouse for managing the entire data-for-AI lifecycle in a single experience,” said Gunnar.
Closing Thoughts
It’s great to see IBM launch this series of products that tackle the complexities of the enterprise data stack for agentic and other AI use cases. While it’s not the first company in the Cloud Wars Top 10 to do this — Microsoft Fabric, ServiceNow’s Workflow Data Fabric, and SAP’s Business Data Cloud are particularly notable examples — it does possess a unique advantage.
In challenging RAG, IBM is, in my opinion, demonstrating the best contender to rival what has been, without a doubt, the most heralded approach to driving AI development. This is a significant step and a massive advertisement for IBM’s watsonx.data lakehouse, serving as a powerful toolkit for data teams looking to create the next wave of innovative applications using proprietary data.
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