Abstract
In the era of information, huge quantities of data became readily available in the hands of decision makers. Big Data is normally referred to sets of data in which they are not just big in terms of size but they also very much various in terms of velocity and variety, this makes such data very hard to be handled through conventional techniques and tools. Because of the fast growth of these data, there is a need for solutions to be studied and provided to enable handling and extracting knowledge and value from such sets of data. Consequently, applications must be opposed with the challenges of Big Data. For this reason, strategy of partitioning the data has a very critical role in the database platforms. Currently, many data partitioning strategies are available and can resolve some issues such as low hot spot, scalability, low performance and so on. In this paper, we discussed advanced partitioning strategies and their implementation.