Microservices have emerged as a software design paradigm where small, autonomous services interact to meet business requirements. However, transitioning from monolithic systems to microservices presents challenges, especially when multiple subdomains share transactional tables to maintain referential integrity across separate databases. Ensuring each microservice handles business data while adhering to ACID properties—namely, atomicity, consistency, isolation, and durability—is crucial. This requires unique, consistent, and low-dependency data from a business domain perspective. Systematic Literature Review serves as a secondary research method aimed at evaluating the existing body of scientific literature. It helps identify existing work, highlight research gaps, and propose new research directions. In software engineering, SLRs offer a comprehensive overview of studied research areas. This article reports an empirical study based on a systematic literature review aimed at identifying modeling techniques for segmenting data structures during microservice design. The review found limited methods to address the appropriate level of data granularity per microservice. These findings highlight a need for further research into processes and methodologies that can effectively handle data segmentation and consistency within microservice architectures.