IBM watsonx.data
The governed data lakehouse that gives AI the context it needs to deliver results you can trust.
Your data, where it lives
watsonx.data accesses and queries data across cloud and on-premises environments without moving or duplicating it, giving AI and analytics workloads a complete, connected view across systems. For organisations with data spread across databases, data lakes, documents, and object storage, this removes the need to consolidate everything into a single platform before AI can start delivering value. Find out more on the IBM website: IBM watsonx.data >
The right engine for every workload
Not every AI or analytics workload should run on the same engine. watsonx.data runs each workload on the most efficient engine for its performance and cost requirements, preventing overprovisioning, improving performance, and keeping costs predictable as usage scales. Multi-engine execution means organisations avoid the compromises of one-size-fits-all platforms as their AI ambitions grow.
Governed at the moment of use
Governance that is applied after the fact is not governance. watsonx.data applies consistent access controls, policies, and lineage tracking across all data and workloads at the moment data is used. So AI systems operate on data that is not just trusted in theory but demonstrably governed in practice. Works alongside watsonx.governance for enterprise AI risk and compliance, and watsonx.data intelligence for cataloguing and data quality.
Open by design
watsonx.data is built on open, standards-based foundations, supporting existing technology stacks and working with new tools and workloads as AI requirements evolve. Open table formats mean data is accessible without proprietary lock-in, and the platform connects across the broader data and AI ecosystem including watsonx Orchestrate for agent workloads and DataStax for vector search and unstructured data.
watsonx.data in action
For organisations trying to scale AI but held back by fragmented data, inconsistent governance, or the cost and complexity of replatforming, watsonx.data is where Dot Group starts the conversation. It sits at the centre of the AI-ready data platform architecture we build for clients, the governed lakehouse layer that connects structured and unstructured data, makes it accessible to AI workloads, and ensures every outcome can be explained and trusted.
Data spread across too many systems to make AI work reliably?
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