Data-Driven Decision Making (D3M) has shown great promise in professional pursuits such as business and government. Here, policy-makers collect and analyze data to make their operations more efficient and equitable. Progress in bringing the benefits of D3M to everyday life has been slow. For example, a student asks, \"If the users pursue an undergraduate degree at this university, what are their expected lifetime earnings?\". Presently there is no principled way to search for this, because an accurate answer depends on the student and school. Such queries are personalized, winnowing down large datasets for specific circumstances, rather than applying well-defined predicates.