Abstract
traditional data analytic might not have the capacity to handle enormous amount of data. Due to the rapid growth of information, solutions need to be contemplated and provided in order to handle and extract value and knowledge from these data sets. Moreover, decision makers should have the capacity to increase significant bits of knowledge from such fluctuated and quickly evolving information. Such esteem can be given utilizing big data analytic, which is the utilization of advanced analytic techniques on big data using MapReduce approach. This paper examines to develop a high performance platform to efficiently analyse big SEER (Surveillance, Epidemiology, and End Results) breast cancer data set using MapReduce to find the recurrence of breast cancer. Keywordscancer; Big data, Classification; Data analytics, MapReduce, SEER.
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