Authors:Â Rahul H Sathawane, Santosh Kumar Sahu
Abstract:Â Big data analytics is the process of examining large and varied data sets -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends; customer preferences and other useful information that can help organizations make more-informed business decisions. Big data is big news and so too is analytics on big data. Technologies for analyzing big data are evolving rapidly and there is significant interest in new analytic approaches such as Hadoop, MapReduce and Hive, and MapReduce extensions to existing relational DBMSs. This paper examines the benefits of big data and the role of the data scientist in deploying big data solutions. It discusses the benefits of Hadoop, MapReduce, Hive, and relational DBMSs that have added MapReduce capabilities. It presents a set of scenarios outlining how Hadoop and relational DBMS technology can coexist to provide the benefits of big data and big data analytics to the business and to data scientists. As an example of the use of MapReduce in a relational DBMS, the paper also reviews the implementation of MapReduce in the Aster Database
Full Issue
| View or download the full issue | PDF 30-42 |