The data that can be extracted from Smart Grids contains a lot of valuable information that would expose hidden opportunities to efficient utilization of existing resources. The data comes in the form of measurements from smart meters/devices. Energy Analytics is irreplaceable for this kind of task. It is a process of collecting data from smart meters/devices both real time and from archival stores and applying some sort of data analysis technique to gain some insight into important correlations, trends, and patterns. This paper offers elaborate discussion on the application of big data in smart grids and describes future prospects for this technology in Kazakhstan. Furthermore, this paper demonstrates a case study of load profiling using the data set that contains energy consumption readings for London households between November 2011 and February 2014. To analyse the data set the K-means clustering algorithm for unsupervised learning is used here. The results of this overview clearly demonstrated the fields where energy analytics can impact the energy segment of Kazakhstan infrastructure and introduces possible ways of overcoming challenges that are present in power systems. However, it is apparent that, in order to realize all these possibilities, it is important to increase the awareness of both government (i.e. the ones to implement the policy) and citizens (i.e. the ones who would make it possible).