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Guide: Why You Need Trustworthy AI Data Fabric

Posted by LPA Software Solutions on May 10, 2022 1:09:00 PM

If you don’t trust the data you’re using, you can’t trust the analytics. The AI lifecycle requires transparency, fairness, robustness, and privacy in data, models, and processes.

With the right tools, you can instill trust in AI and deliver the outcomes you need:

  1. Trust in models is essential for machine learning, explainability, fairness, and monitoring.
  2. Trust in process addresses the need for AI governance with automation at each stage of the AI lifecycle.

To fully trust your data, you need a comprehensive view that is governed and prepared properly for analysis. No amount of digital magic can overcome poor data. You need a reliable way to track data lineage and enforce policies as part of your governance to build a solid data foundation.

Nearly three-quarters of AI users say that data access is a challenge, according to 451 Research.

Yet, the strength of AI models depends on being to aggregate accurate data from multiple sources, including internal and external sources across public and private clouds.

Achieving success with AI and ML requires trust in data, models, and processes.

This guide shares how collaborating on the IBM Cloud Pak® for Data platform allows trustworthy AI lifecycle management that reduces complexity, improves productivity, and mitigates bias.

However your data is distributed across on-premises, cloud, multi-cloud, or hybrid cloud landscape, you can eliminate data siloes and enforce a governance framework that automates data protection policies.

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Are you ready to learn more about data fabric and how trustworthy AI can benefit your organization? Simply fill out the form to get Your Guide on Why You Need a Trustworthy AI Data Fabric.  

Topics: Cloud Pak, Content, AI, Data Fabric

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