Representative End User Clients
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IBM announced new offerings to its Watson Data Platform, including data cataloging and data refining, which is designed to make it easier for developers and data scientists to analyze and prepare enterprise data for AI applications, regardless of its structure or where it resides. By improving data visibility and helping to better enforce data security policies, users can now connect and share data across public and private cloud environments.
Addressing the challenges of building AI functionality into apps, IBM has expanded the functionality of its Watson Data Platform, an integrated set of tools, services, and data on the IBM Cloud designed to enable data scientists, developers and business teams to gain intelligence from the data most important to their roles, as well as easily access services, like machine learning, AI, and analytics.
Specifically, this expansion includes:
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New Data Catalog and Data Refinery offerings, which bring together datasets that live in different formats on the cloud, in existing systems and in third party sources; as well as apply machine learning to process and cleanse this data so it can be ingested for AI applications;
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The ability to use metadata, pulled from Data Catalog and Data Refinery, to tag and help enforce a client’s data governance policies. This gives teams a foundation to more easily identify risks when sharing sensitive data.
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The general availability of Analytics Engine to separate the storage of data from the information it holds, allowing it to be analyzed and fed into apps at much greater speeds. As a result, developers and data scientists can more easily share and build with large datasets.