Despite the increasing interest in data analytics applications within postgraduate education research, there remains a significant gap in research dedicated to exploring mixed methods research for such investigations. This study undertook to bridge this gap by exploring the application and use of mixed methods research to examine data analytics within postgraduate education research. The research specifically explored the prevalence and characteristics of existing mixed methods research, and compared the unique insights they offer within this specific research domain. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the researchers conducted a systematic search across five databases, resulting in the inclusion of 22 relevant publications. Data were systematically extracted, capturing study characteristics, methodological approaches, data analysis techniques, key findings, and identified limitations for analysis. This study underscored the value and use of mixed methods research in advancing data analytics research within the context of postgraduate education. Thus, by integrating quantitative and qualitative data, this methodology generates robust, triangulated findings to tackle complex research questions. This leads to actionable insights that optimise student learning experiences and support mechanisms, fostering critical research skills, problem-solving abilities, and data-driven expertise.