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Cloud computing become most adoptable technology over the past few years, it is widespread for both at organizational level or for the person who use the services that are offered in the cloud. There are several technocrats currently researched on cloud related issues and soon cloud represents the modern computing. The cloud gave the prospect for the enterprise and allowing them to center on their work by providing hardware and software solution without developing them own. Now a day the database has also moved to cloud computing so we will look into the fine points of database as a service and it's servicing. While storing data on cloud there is a need to balance the load on datacenters because if user base always sends request on single data center then it becomes overloaded so load balancing techniques are applied to manage this problem. To manage geographic distribution in terms of computing servers and data workloads a tool termed as CloudAnalyst is used which is based on cloudsim technique. CloudAnalyst helps developers with the vision of distributing applications among cloud infrastructures. Currently tool having three algorithms for load balancing round robin, throttled load balancer, equally spread current execution and the proposed algorithm is weighted round robin which works better as comparison to round robin in various aspects.

As the Volume of the data produced is increasing day by day in our society, the exploration of big data in healthcare is increasing at an unprecedented rate. Now days, Big data is very popular buzzword concept in the various areas. This paper provide an effort is made to established that even the healthcare industries are stepping into big data pool to take all advantages from its various advanced tools and technologies. This paper provides the review of various research disciplines made in health care realm using big data approaches and methodologies. Big data methodologies can be used for the healthcare data analytics (which consist 4 V’s) which provide the better decision to accelerate the business profit and customer affection, acquire a better understanding of market behaviours and trends and to provide E-Health services using Digital imaging and communication in Medicine (DICOM).Big data Techniques like Map Reduce, Machine learning can be applied to develop system for early diagnosis of disease, i.e. analysis of the chronic disease like- heart disease, diabetes and stroke. The analysis on the data is performed using big data analytics framework Hadoop. Hadoop framework is used to process large data sets Further the paper present the various Big data tools , challenges and opportunities and various hurdles followed by the conclusion.