In this study, we present a framework for scaling Data & Analytics initiatives and use cases. Unlike existing studies, we focus on practical implications and draw attention to the comprehensive combination of multiple perspectives on scale and scaling. We develop a framework consisting of scaling challenges, scaling enablers and scaling approaches for D&A use cases and initiatives divided into four scaling perspectives: development, governance, business and use case lifecycle. The framework was developed using a grounded theory approach with 12 expert interviews from different large manufacturing companies. Based on the findings, we present practical implications and develop a future research agenda.