Dr. Mario Callegaro ’02 and ‘07, senior research scientist at Google UK, visits the University of Nebraska-Lincoln College of Business Monday, November 20 at 4 p.m. to present “The Role of Surveys in the Era of ‘Big Data’”. In his talk, Callegaro discusses the relationship between surveys and big data to help researchers decide what data sources, or combinations of them, are best to serve their research objectives. The presentation takes place in Howard L. Hawks Hall CoB 231. The events is free and open to the public.
Callegaro earned his Ph.D. in survey research and methodology (SRAM) at Nebraska with Dr. Robert Belli in 2007. He also completed a master of science degree in survey research in the same program.
One of Callegaro’s primary themes involves distinguishing perspectives about errors in surveys and in big data as a key starting point when looking at combining the two sources of data. By showing trends in survey practices in recent years, he also disputes the notion that surveys are in an existential crisis due to big data advancements, and provides an alternative view where the two working together create better values.
A second theme of the talk will be devoted to privacy, confidentiality and data transfer, which are crucial when working on personal identifiers. Given the new tools and technologies available in this era of big data, Callegaro provides his recommendations for researchers regarding news skills and training needs.
Prior to joining Google, he worked as a survey research scientist for GFK-Knowledge Networks. He serves as the associate editor of Survey Research Methods and a member of the editorial board of the International Journal of Market Research. His research expertise includes web survey design, smartphone surveys, cellphone surveys and questionnaire design.
As a former student in the Nebraska SRAM program, he gained experience learning about best innovative practices in the collection and analysis of regional, national and international survey data. The program covers collection and analysis of other forms of data, and the use of all data to support understanding and decision making in multi-disciplinary settings.
For more information on the SRAM program, visit: sram.unl.edu