IBM Corp. is looking to make data more accessible for its Watson Data Platform so it can be used by applications that leverage artificial intelligence.

The company on Thursday said it’s adding new data cataloging and refining features to Watson that will make it easier for developers and data scientists to prepare and analyze data for AI applications. The new capabilities make it easier for users to connect and share data across public and private clouds, and are part of a broader expansion of IBM’s data governance products.

The IBM Watson Data Platform is a cloud-based service that integrates various tools to help data scientists and others gain intelligence from their data, and to access AI, analytics and machine learning services.

The new Data Catalog and Data Refinery tools help to bring together data that exists in different formats and various places such as the cloud or on-premises and make it accessible to users. They can also be used to cleanse this data so it’s ready for AI-based applications to use. Other advantages include being able to use metadata to tag and enforce data governance policies to ensure data remains secure.

IBM is also announcing general availability of its Analytics Engine, which separates data storage from the information it holds so it can be fed to AI apps much faster than before, the company said. The company said the new capabilities should help to eliminate one of the main obstacles that AI-based application developers face, which is making sense of complex data that’s housed in different locations.

Better governance

Data governance is a growing issue for enterprises that are grappling with rapidly growing data volumes. IBM is addressing that need with extensions to its Unified Governance Platform that make it easier for organizations to find and classify data. The InfoSphere Information Server now provides a single view of the Unified Governance Catalog, which is used to define common data descriptions. Having a single view makes it easier for users to find and understand their data across the organization, IBM said. The company also reworked the Datastage Designer tool for defining tables and metadata services with an approach that recognizes and suggests usage patterns.

A new Analytical Master Data Management tool provides self-service features for visualizing, exploring and correlating data sources dynamically. A function called domain “consent management” is aimed at companies that are preparing to conform to the General Data Protection Regulation rules that are set to go into effect in the European Union next May. Users can view and manage various aspects of the consent process defined in the GDPR requirements.

IBM also updated its Industry Data Models with GDPR in mind. These pre-designed business and technical data models can be used to speed the development of business intelligence applications around data that has already been identified. Support for GDPR domain-specific terms has been added, along with an index of industry-specific vocabulary that bridges the language gap between regulators and vertical industries.

“The key to AI starts with a strong data foundation, which turns the volume and velocity of incoming data from a challenge into an asset,” said Derek Schoettle, general manager of IBM Watson Data Platform. “For companies to innovate and compete with AI, they need a way to grasp and organize data coming in from every source, and to use this complete index of data as the backbone of every decision and initiative.”

Image: IBM