In this paper I have analyzed and improved MM Cube Technique to better time-efficiency. MM Cube that compute Iceberg Cubes by factorizing the lattice space according to the frequency of values. This approach, different from all the previous dimension-based approaches where the importance of data distribution is not recognized, partitions the cube lattice into one dense subspace and several sparse Subspaces. MM-Cubing is efficient and achieves high performance over all kinds of data distribution compare to previous cube techniques. Shared array is used as Data Structure in existing MM Cube. In this paper I have presented MM cube with tree as Data Structure to improve Time-Efficiency. Tree is used Approiry Pruning Strategy which cut down the node, which doesn’t satisfy the Iceberg condition. So, it reduces traversal time, which minimizes cube computation time and such a way it tries to solve fundamental issue of efficient cube computation in Data Warehouse and OLAP System.