As data continues to expand, it is becoming more problematic to provide performant query access to entire datasets. The data twin, implemented as a data product, is a representative subset of the entire population that is significantly smaller. It can be reliably generated and consumed for inference and supporting a range of use cases, including exploratory, estimation and hypothesis testing. In this session, attendees will learn what a data twin is and how to implement data twins to support AI initiatives.
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Speaker
Michael Gonzales
1
talks
Sr. Director Analyst for Data Management and Technology
Bio from: gartner-data-analytics-us-2026
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