The 21st century has become an era of “big data” in ecology and evolution, but inference remains limited when drawn from classical statistical approaches based on single data sets. With the advent of integrated data analysis such as data reconciliation and data fusion, researchers are now able to combine data sets that directly and indirectly inform common processes (e.g., the collection of demographic and environmental parameters that give rise to changes in abundance over space and time). Current integrated analyses are flexible to include numerous data types and are accessible for practitioners to address critical knowledge gaps in ecology and evolution, such as species distributions informed by citizen science and traditional abundance data, the demographic trade-offs in life histories, and the demography of the full annual cycle based on newly estimable rates. These properties allow for more detailed and robust insights into the processes that drive ecological and evolutionary dynamics, which can better inform conservation, natural resource management, and planning for cultural challenges in the 21st century such as climate change. This session will highlight the breadth and scope of recent developments in data integration for addressing novel topics in ecology, evolution, and natural resource management.