In the wake of the increasing surge in business applications of data analytics, machine learning, and artificial intelligence to support key decision-making processes, research on business analytics (BA) and decision support systems (DSS) has continuously branched into new topics and approaches. However, as both research streams have long-standing histories, it can be difficult for information systems researchers, DSS designers, business analysts, and managers to apply existing DSS research to increase data and analytics-heavy information systems. This paper presents a conceptual framework to show the relevance of received DSS approaches in BA through a systematic literature review of the DSS and BA literature. The framework shows how DSS approaches can be applied at different stages of the data analytics process and how combining multiple approaches is necessary to support all dimensions of analytics-based decision-making.