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Using AI, Mathematics, and Statistics to Find Similar Data in Massive Data Ecosystems

Eric Warner Eric Warner | Senior Manager, AI Engineering | Collibra

Enterprise data governance is an increasingly complex space growing rapidly at scale. Humans need software to help process the amount of information, make meaningful inferences, and illuminate areas of interest and value. Opportunities for automation and innovation far exceed development capacity and budget, so development teams must work with economies of scale as a critical lever in delivering impact without breaking the bank.

Collibra uses data samples to find patterns in tables and columns that suggest similar data, using a combination of AI, mathematics, and statistics to balance cost and performance—and it all runs for pennies on the dollar. Learn how Collibra built this AI algorithm that backs two features today and more in the future, helping business users find relevant data sets and technical users manage the cost, risk, and waste of duplicate data sets.

Eric Warner
Eric Warner
Senior Manager, AI Engineering | Collibra

Eric Warner is the Senior Manager of the Artificial Intelligence team at Collibra. He leads a group of Data Scientists, AI Engineers, and Machine Learning Operations Engineers who discover, develop, and sustain AI/ML applications in production. The team also partners across the business to scale AI tools & technologies as well as the power of Generative AI and Large Language Models.
Prior to joining Collibra, Eric received a PhD in Intelligent Systems and a Masters in Electrical Engineering from the University of Michigan. He also spent a number of years at Raytheon Technologies, serving as a Data Scientist, Technical Lead, and Senior Manager with a focus on AI applications in a factory space. As part of these roles, he garnered experience in Image Classification, Time-Series Analysis, Reinforcement Learning, and Computer Vision.