IBM has expanded the functionality of its Watson Data Platform to include data cataloguing and data refining, to help developers and data scientists build AI applications.
On Thursday, IBM announced new capabilities for its Watson Data Platform that make it easier for developers and data scientists to analyze and prepare enterprise data for artificial intelligence (AI) applications.
By 2018, nearly 75% of developers will build AI functionality into their apps, according to an IDC report. However, this requires wading through increasingly complex data that lives in different places, and must be continually and securely ingested, according to an IBM press release.
In response to this challenge, Watson will now include data cataloging and data refining, to improve data visibility and better enforce data security policies so that users can more easily share information across public and private cloud environments.
"We are always looking for new ways to gain a more holistic view of our clients' campaign data, and design tailored approaches for each ad and marketing tactic," Michael Kaushansky, chief data officer at global advertising and marketing consultancy Havas, said in the release. "The Watson Data Platform is helping us do just that by quickly connecting offline and online marketing data."
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For example, Havas recently launched a test for an automotive client with the goal of connecting customer data, advertising information in existing systems, and online engagement metrics to better target the right audiences at the right time, Kaushansky said in the release.
The data catalog and data refinery offerings will bring together datasets that live in different formats on the cloud and in existing systems and third party sources. Watson will use machine learning to process and cleanse the data, so it can be more easily ingested for AI applications.
Developers and data scientists will also be able to use metadata pulled from theses two sources to tag and help enforce a client's data governance policies--giving teams the ability to more easily identify risks when sharing sensitive information.
IBM also announced the general availability of its Analytics Engine, which can separate the storage of data from the information it holds, allowing it be be analyzed and ingested into apps much faster. This will help developers and data scientists to more easily share and build with large datasets.
"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," Derek Schoettle, general manager of IBM Watson Data Platform, said in the release. "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."
In addition to the Watson news, IBM also announced plans to extend its Unified Governance Platform with new capabilities, to help companies prepare for increasing governance and regulatory requirements, such as GDPR. They include the ability to have a single view of the Unified Governance Catalog for both structured and unstructured information. It also modified the look of its Datastage Designer with a cognitive design that can recognize and suggest usage patterns, to speed the development of data integration flows.
The 3 big takeaways for TechRepublic readers
1. IBM announced new capabilities for its Watson Data Platform that make it easier for developers and data scientists to analyze and prepare enterprise data for artificial intelligence (AI) applications.
2. Watson will now include data cataloging and data refining, to improve data visibility and better enforce data security policies so that users can more easily share information across public and private cloud environments.
3. IBM also announced plans to extend its Unified Governance Platform with new capabilities to help companies prepare for increasing governance and regulatory requirements.
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