IBM’s watsonx.data could simplify agentic AI-related data issues

IBM has updated its data management platform — watsonx.data — to simplify data challenges related to agentic AI and include capabilities and tools that could help enterprises manage, analyze, and govern data more effectively.

IBM said enterprises’ biggest hurdle to unlock agentic AI and generative AI’s full potential is unstructured data and not inferencing costs.

“Many enterprises are not addressing the root problem. They are focused solely on the generative AI application layer, rather than the essential data layer underneath. Until enterprises fix their data foundation, AI agents and other generative AI initiatives will fail to deliver their full potential,” Edward Calvesbert, VP of product management for watsonx, wrote in a blog post.

Agentic AI or applications underpinned by it that can complete tasks without manual intervention while learning from new data are attracting the attention of enterprises looking to automate more work, and cloud services providers, such as IBM, want to capture this growing market.

Unifying data and governance across multiple formats, clouds

The new updates, which are an effort in that direction, comprise new capabilities inside watsonx.data that bring together an open data lakehouse with data fabric capabilities, such as data lineage tracking and governance, to help enterprises have a single control pane for managing data across formats and multiple clouds.

The combo of an open data lakehouse along with data fabric capabilities should help IBM customers simplify their data stack, said Bradley Shimmin, lead of the data and analytics practice at The Futurum Group.

“Especially for those customers who are looking to use more of their data in powering AI solutions without sacrificing important governance and management capabilities like lineage and cataloging to better understand the origin, movement, and transformation of data across disparate sources and deployment models (cloud, premises, hybrid),” Shimmin added.

New tools for data orchestration and analysis

As part of the updates, IBM has added new tools to watsonx.data for data orchestration and analysis, both of which will also be available as standalone products.

For orchestrating data across formats and pipelines, IBM has introduced a single-interface tool — watsonx.data integration.

Although IBM didn’t provide more details about the tool, Shimmin believes that it makes sense for IBM to invest in the tool as it wants to develop watsonx.data as a platform of choice for customers to create their central data repository.

However, he pointed out that IBM’s efforts in the direction of delivering a single tool to locate, integrate, catalog, transform, and instantiate data as a product are not unique,e and most data lakehouses and broader data platforms have tried to reach the same goal.

“The tool or its capability is mission-critical for AI-aspiring businesses right now. And IBM’s new tool is not yet on par with products from Informatica, Alteryx, Snowflake, Google, and AWS,” Shimmin explained.

For data analysis and extracting insights from data using AI, IBM has added the watsonx.data intelligence tool.

IBM hasn’t provided additional details about this tool as well, but Shimmin believes that the new tool cannot be compared with similar tools from other BI software vendors and data lakehouse providers, as its purpose is to serve the data integration lifecycle.

However, he pointed out that the new intelligence tool “appears to be uniquely tuned” to directly address the challenge of working with unstructured data, especially in highly distributed environments and in supporting diverse data formats.

“This tool is really tuned to help not just developers but a pretty wide array of user roles, such as data engineers, data scientists, data analysts, and even business users,” Shimmin added.

The new updates to watsonx.data, along with the new tools, are expected to be available in June.