Towards Efficient Big Data

Currently, the generated data flow is growing at a high rate resulting to the problem of data obesity and abundance, but yet a lack of pertinent information. To handle this Big Data, Hadoop is a distributed framework that facilitates data storage and processing. Although Hadoop is designed to deal with demands of storage and analysis of ever-growing Data, its performance characteristics are still to improve. In this regard, many approaches have been proposed to enhance Hadoop capabilities. Nevertheless, an overview of these approaches shows that several aspects need to be improved in terms of performance and data relevancy. The main challenge is how to extract efficiently value from the big data sources. For this purpose, we propose in this paper to discuss Hadoop architecture and intelligent data discovery, and propose an effective on-demand Big Data contribution enabling to process relevant data in efficient and effective way according to the stakeholderu0027s needs, and aiming to boost Data appointment by integrating multidimensional approach.