IBM this week extended the scope of its platform for managing data to add an ability to unify governance, quality, lineage tracking and sharing in addition to simplifying data integration.

Edward Calvesbert, vice president for IBM watsonx, said these extensions to the watsonx.data portfolio are specifically designed to enable IT teams to more easily manage massive volumes of unstructured data that is now required to drive, for example, artificial intelligence (AI) applications.

For example, IBM watsonx.data integration provides a control plane through which data engineers can orchestrate data movement across a range of methodologies, including extract transform and load (ETL) and extract, load and transform (ELT) tools that move bulk data in batches, real-time streaming and data replication. Available also as a standalone product, IBM watsonx.data integration also makes it simpler to apply data observability capabilities across both unstructured and unstructured data, noted Calvesbert.

A Watsonx.data intelligence tool, meanwhile, makes use of artificial intelligence (AI) to unify data management across a hybrid IT environment in a way that makes it simpler to discover, curate, govern and manage data, he added.

The overall goal is to make it simpler to access, enrich, manage and govern the high-quality data needed to drive the next generation of AI applications, said Calvesbert. The challenge organizations are encountering is that much of their data is today stored in isolated silos that can make it difficult to expose the right data at the right time to AI models, he added.

That’s critical because the only way to drive a meaningful return on the investment made in AI is to be able to safely expose proprietary data in ways that enable enterprise IT organizations to granularly control how specific sets of data are shared, noted Calvesbert.

These latest additions to the IBM portfolio follows the acquisition of DataStax, a provider of a database-as-a-service platform based on the open source Cassandra software being advanced under the auspices of the Apache Software Foundation (ASF).

IBM has committed to later this month launching an AI analytics agent to surface business intelligence (BI) insights via a natural language interface. Dubbed watsonx BI, this offering will also be made available as a standalone offering or via the watsonx platform.

Additionally, IBM is integrating the Gluten Accelerated Spark framework for offloading SQL queries into watsonx.data portfolio and, previously, IBM added agentic AI tools that make it simpler to orchestrate and govern data.

It’s not clear to what degree the rise of AI is driving a renewed appreciation for data management, but the one thing that is certain is an AI application is only going to be as accurate as the data that is exposed to them. As such, being able to curate, orchestrate and govern data effectively has never been more crucial.

Of course, the degree to which organizations can effectively manage data varies widely. However, in the final analysis the success of any AI initiative will come down to the quality of the unstructured and structured data an organization is able to effectively aggregate and manage.