In today’s data-driven business environment, organizations face the challenge of effectively leveraging vast amounts of data for decision-making. Business Intelligence and Analytics (BI&A) systems are crucial for generating insight, but often fail to meet the diverse needs of users with different contextual, individual, and task-related characteristics. Personalization has emerged as a promising concept to better align BI&A systems with individual user needs. However, research on personalization in BI&A systems remains fragmented, lacking a structured framework to classify common personalization characteristics. This article addresses this gap by providing a comprehensive overview of personalization in BI&A research. Specifically, we (1) conduct a systematic literature review, (2) develop a morphological box to conceptualize personalization characteristics, and (3) perform a cluster analysis to identify key research streams. Based on an analysis of 43 articles, this study synthesizes existing literature, conceptualizes personalization in BI&A, and proposes four future research directions.