This session focuses on how to extend data quality and data lineage programs to ensure both data inputs and outputs of AI models are reliable, including leveraging ML for DQ and ensuring that the data used for training AI systems is of high quality to generate appropriate outputs. The provenance of data is important for the trustworthiness of data models to ensure the correct source is reliable.
Bobbi Caggianelli, Collibra, Manager, Sales Engineering
Ioana Mazare, UPS, VP, Enterprise Data Strategy
Prasannal Nithyanandam, VW Credit, Inc., Head of Data & Advanced Analytics, Sr Director