Big Streaming Data Buffering Optimization

With increasing content of data that is being created around the globe, there are at times the need for analyzing the data real time. Few of the constraints that come with real-time analysis of such huge amounts of data are time and infrastructure. In cases where time of analyzing the data is a key factor, analysis cannot be done on all of the data that is being generated real-time as the speed of stream overweighs the speed of the processing the same. When time is not that important of a factor, it calls upon a very high end infrastructure to process heavy incoming traffic of data. In such scenarios where the entire population (real-time streaming data) cannot be analyzed and cases where the prior information about the population size is not available, Sampling of the population can be used as an effective technique and the processing can be done on sampled data by maintaining possible error at the least.