Background Cloud computing promises dependable services offered through next-generation data centres based on virtualization technologies for computation, network, and storage. Big Data Applications have been made viable by cloud computing technologies due to the tremendous expansion of data. Disaster management is one of the areas where big data applications are rapidly being deployed. This study looks at how big data is being used in conjunction with cloud computing to increase disaster risk reduction (DRR). This paper aims to explore and review the existing framework for big data used in disaster management and to provide an insightful view on how cloud-based big data platform towards DRR is applied. Methods A systematic mapping study is conducted to answer four research questions with papers related to Big Data Analytics (BDA), cloud computing and disaster management ranging from year 2013 to 2019. Results Total 26 papers were finalized after going through five steps of systematic mapping. Findings are based on each research questions. Conclusion To conclude, a specific study on big data platform on the application of disaster management in general is still limited. Lack of study in this field is opened for further research sources., {"references":["Alani, M. M., Alani, & Wheeler. (2018). Applications of Big Data Analytics (Vol. 219). Springer.","Emmanouil, D., & Nikolaos, D. (2015). Big data analytics in prevention, preparedness, response and recovery in crisis and disaster management. In The 18th International Conference on Circuits, Systems, Communications and Computers (CSCC 2015), Recent Advances in Computer Engineering Series, Vol. 32, pp. 476–482.","Muhammad Arslan, Ana Roxin, Christophe Cruz, Dominique Ginhac. A Review on Applications of Big Data for Disaster Management. The 13th International Conference on SIGNAL IMAGE TECHNOLOGY & INTERNET BASED SYSTEMS, Dec 2017, Jaipur, India.","International Strategy for Disaster Reduction, United Nation Website. https://eird.org/esp/acerca-eird/liderazgo/perfil/what-is-drr.html). Last access on 5 September 2021.","Abdullah, Mohammad Fikry et al. \"Big Data Analytics Framework for Natural Disaster Management in Malaysia.\" IoTBDS (2017)","D. Puthal, S. Nepal, R. Ranjan and J. Chen, \"A Secure Big Data Stream Analytics Framework for Disaster Management on the Cloud,\" 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2016, pp. 1218-1225, doi: 10.1109/HPCC-SmartCity-DSS.2016.0170.","X. Hu, J. Gong, E. G. Renard and M. Parashar, \"Two-Stage Framework for Big Spatial Data Analytics to Support Disaster Response,\" 2019 IEEE International Conference on Big Data (Big Data), 2019, pp. 5409-5418, doi: 10.1109/BigData47090.2019.9005613.","P. Tin, T. T. Zin, T. Toriu and H. Hama, \"An Integrated Framework for Disaster Event Analysis in Big Data Environments,\" 2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2013, pp. 255-258, doi: 10.1109/IIH-MSP.2013.72.","S. J. Baillarin et al., \"Perspectives for VHR Big Data Image Processing and Analytics Toward a Dedicated Framework for Major Disaster and Environment Monitoring from Space,\" IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019, pp. 5401-5404, doi: 10.1109/IGARSS.2019.8900159.","Carrington, D. (2001). Software engineering tools and methods. SWEBOK,","Humphrey, W. S. (1989). Managing the software process. Addison-Wesley Longman Publishing Co., Inc.","IEEE 15939-2017 - ISO/IEC/IEEE International Standard - Systems and software engineering--Measurement process.","Dori, D. 2002. Object-Process Methodology: A Holistic System Paradigm. New York, NY, USA: Springer.","Bailey, J., Budgen, D., Turner, M., Kitchenham, B., Brereton, P. & Linkman, S. (2007), Evidence relating to object-oriented software design: A survey, in 'Proc. of the 1st Int. Symp. On Empirical Software Engineering and Measurement (ESEM 2007)', pp. 482–484.","Kitchenham, B. & Charters, S. (2007), Guidelines for performing systematic literature reviews in software engineering, Technical Report EBSE-2007-01, School of Computer Science and Mathematics, Keele University.","Wieringa, R., Maiden, N. A. M., Mead, N. R. & Rolland, C. (2006), 'Requirements engineering paper classification and evaluation criteria: a proposal and a discussion', Requir. Eng. 11(1), 102–107."]}