An important application of outlier detection like normal and abnormal action detection, animal behaviour alter, etc. It’s a hard issue since global data about information regarding data divisions must be called to verify the outliers. In this paper, I discussed the proposed approach in the research area. In the proposed work, I divide the data into two clusters, i.e., Cluster1 and Cluster2. We implement K-means clustering to divide the data into two sections, detected or not detected data. We optimize the outlier data with the bacteria Foraging Optimization approach. In BFOA, algorithm based on further steps: (i) population Size (ii) Rotation (tumble and swim) (iii) dispersal (iv) reproduction of the abnormal data. This means BFOA optimizes the relevant data. The classification algorithm is used to classify the outliers based on the training and testing phase. In this technique, to use and optimize the communication cost. Later, grouped data in a single position for centralized processing.

Gathering and breaking down enormous volumes of unique datasets are significant difficulties that emerged from the rise of Big Data in the field of wellbeing. However, the innovation of Big Data is additionally connected with promising open doors which can give an improvement of execution and help of advancement in associations. Since deciding the lifetime is a handy methodology in regards to an acknowledgment of wonder and its administration, this paper planned for recognizing the difficulties and chances of overseeing Big Data in the zone of wellbeing at various phases of the lifecycle of Big Data. This article is an organized survey. After an underlying survey, 6 stages were identified in the lifecycle of Big Data, at that point, the procedures of conventional information were quickly checked on in each stage, and the difficulties related to the development of Big Data and the answers for their ideal administration were talked about. This is study offers an expansive diagram of the coming of Big Data in the wellbeing area and gives a reasonable and precise image of the procedures when its development through a near based review in each stage. The article brings up developments and present-day strategies for assortment, pre-preparing, and examination of Big Data just as the procedure of information extricating. It likewise depicts distributed computing applications in the capacity and arrival of Big Data. Ends: Our discoveries show that administration of Big Data in wellbeing, in light of its lifecycle, is ingenious for chiefs and arrangement creators, so as to profit by the mechanical highlights of Big Data with an administrative methodology, to assess difficulties, to apply imaginative arrangements at each period of Big Data development, and to progress towards another degree of advancement, aggressiveness, and profitability.