Decades of reductionist scientific approaches have led to spectacular progress and the proliferation of biological sub-disciplines, each spawning its own technical and social practices regarding data. This fragmented landscape poses substantial hurdles to the multi-disciplinary approaches needed to address pressing societal challenges. Data integration is key to the reintegration of biology and the pursuit of global questions such as climate change, biodiversity loss, and sustainable ecosystem management. Here, we define the primary challenges in data integration and present a vision for a Data as a Service (DaaS) oriented architecture that enables frictionless data reuse, hypothesis testing, and discovery. The proposed data integration infrastructure includes standards development, a suite of tools and services, and strategies for education and sustainability.