September 24, 2024
Many organizations are planning applications for generative AI, but for AI to be successful, the organization’s data must be trustworthy.
As organizations continue their journey to generative AI, new challenges around data trust and quality will emerge. Enterprises will need to be able to evaluate sensitive unstructured data—determining if it is unique and valid, and whether its context is understood. Unstructured data may lack complete and clear metadata; its lineage will also need to be addressed.
TDWI VP and senior research director Fern Halper, Ph.D., recently spoke with Zeashan Pappa, global lead for data governance at Databricks, and Rik Tamm-Daniels, group vice president, strategic ecosystems and technology at Informatica, about this topic. Their discussion covered the evolving data landscape, the core pillars for trusted data, the importance of data quality, and using retrieval-augmented generation to help build trusted generative AI applications.
Download this Digital Dialogue today to read the highlights of this discussion!