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The term big data has many meanings. From an international perspective, I’ll discuss some types and their potential use in child development research: large scale surveys collected for other purposes than developmental science, and administrative records. I address developmental scientists with little previous experience of big data. Such data can provide venues for creative research designs expanding work previously done in small-scale data. I will cover: a) Motivational examples, including testing effects of programs or policies, testing theories about developmental processes, and contextualizing smaller datasets and addressing broader developmental frameworks, like socio-ecological theory; b) Where to find and how to link big data sources, including administrative and population records, data depositories; c) What it takes to use big data sources, including psychometrics, programming skills, causal and longitudinal modeling techniques. I conclude that the added value of big data for developmental science is primarily in strengthening internal and external validity.