Optimized data analysis in cloud using BigData analytics techniques

Because of the huge reduce in the overall investment and greatest flexibility provided by the cloud, all the companies are nowadays migrating their applications towards cloud environment. Cloud provides the larger volume of space for the storage and different set of services for all kind of applications to the cloud users without any delay and not required any major changes at the client level. When the large amount of user data and application results stored on the cloud environment, will automatically make the data analysis and prediction process became very difficult on the different clusters of cloud. Whenever the used required to analysis the stored data as well as frequently used services by other cloud customers for the same set of query on the cloud environment hard to process. The existing data mining techniques are insufficient to analyse those huge data volumes and identify the frequent services accessed by the cloud users. In this proposed scheme trying to provide an optimized data and service analysis based on Map-Reduce algorithm along with BigData analytics techniques. Cloud services provider can Maintain the log for the frequent services from the past history analysis on multiple clusters to predict the frequent service. Through this analysis cloud service provider can able to recommend the frequent services used by the other cloud customers for the same query. This scheme automatically increase the number of customers on the cloud environment and effectively analyse the data which is stored on the cloud storage.