A focus on the most efficient method of data management is required in this case. When it comes to cloud data storage, Big Table and Data Store are two options that work in distinct ways. In order to achieve our goals, it must make use of the appropriate technologies. One of the newest technologies to gain pace in recent years is cloud computing. Rather of relying on local computers, data and software are stored and sent via the internet with this architecture. Cloud resource management is a difficulty since demand is always changing and there are so many concurrent users. Cloud resource management is complicated by server sprawl, a problem that is all too typical in data centres. Overcrowding on servers results in underutilization because of the need for more resources that aren't justified by workload. In this thesis, effective resource management may be used to successfully consolidate servers in cloud data centres. All nodes are housed inside their own virtual machines as a result of the thesis' design of a cost matrix technique. It is possible to maximise the memory of each node by utilising this method, which leaves the rest of the nodes free for other processes to utilise. Virtualization technology is used to allocate and relocate virtual computers from real ones in order to reduce downtime. It was able to reduce server costs and downtime by using the best fit concept. To avoid wasting resources, virtual machines are placed in memory that has spare space and then relocated when the memory is full. The load-balancing hotspot algorithm is also becoming better.