Big data analytics tools a review

Abstract

Big data is the hottest trending term all over the globe and the internet. Big organizations are trying to make use of the large amounts of data collected and stored by them in big memory storages. Further large amounts of data is being produced every millisecond all over the world from users of computing devices, from satellites of all kinds, from scientific research, from governments, from big organizations that deal with huge number of customers especially financial institutions and many more. These data lie there for exploration and exploitation to gain more knowledge or rather intelligence and turning out them into wisdom for better decision making. Traditional data mining tools are not able to handle this big data. Hadoop and MapReduce are the first of the kind of tools that are being used to handle big data. Additional data mining and machine learning capabilities have been added to Hadoop and MapReduce through various plug-ins by different open source as well as vendor tools for big data analytics (BDA). Further big organizations have and are in the process of creating BDA tools most of which come with a price tag. This study gives a short review of the available BDA tools taking into consideration different characteristics of these tools. Possible solutions for existing challenges related to big data analytics are discussed.