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Data fusion is the process of getting data from multiple sources in order to build more sophisticated models and understand more about a project. It often means getting combined data on a single subject and combining it for central analysis.
Various types of data fusion work in different ways. Experts identify low, intermediate and high-level data fusion – and likewise distinguish geospatial types of data fusion from other types of data fusion. Another specific type of data fusion is called “sensor fusion” where data from diverse sensors are combined into one data-rich image or analysis.
Data fusion is broadly applied to technologies, for instance, in a research project, scientists might use data fusion to combine physical tracking data with environmental data, or in a customer dashboard, marketers might combine client identifier data with purchase history and other data collected at brick-and-mortar store locations to build a better profile.
Data fusion also involves a level of concrete definition from something called the Joint Directors of Laboratories Data Fusion Group which produces six levels for a data fusion information group model: