Research supervision is one of the important aspect in academic quality assurance and the sustainbility of the science itself. However, there is lack of attention based on research literature and evidence of good practice on research supervision from the context of academic integrity in higher education. This study aims to develop a data-driven decision making strategy in supervisor selection for post-graduate program based using research projects data. Apart of that, the researchers reviewed the indicator of academic integrity in research supervisory from program standards in masters and doctoral degree by Malaysia Qualification Agency (MQA), international recommendation by UNESCO and Islamic principles according to the roles of the supervisor, administrator and student in the context of research supervisory. This study adopted data analytics and visualization technique using cloud-based collaborative platform as a research method for data acqusition, processing and analyzing the data. The researchers acquired the research projects profile data registered in the institutional database in Universiti Malaysia Pahang from Department of Research and Innovation as a case study. We categorized and mapped the research profile according to Malaysian Research and Development Classification System (MRDCS) code. The combined data was been analyzed and visualized to specific online dashboard to indicate the research experience in fraction of years as a metric. The researchers evaluate the characteristics of the dashboard based on the academic integrity indicators from MQA, UNESCO and Islamic principles as our measures. The result shows that there is a potential usefulness of the proposed strategy in assuring academic integrity for supervisor selection in post-graduate programmes. This novel approach has a potential impact on academic integrity in higher education which can be adopted at larger scale by higher education institution in Malaysia.