An Insight on Big Data Analytics Using Pig Script

Abstract Today, the advancement in organizations across public and private sectors have made unprecedented growth in data, From the analysis it’s predicted that the digital universal data will be 35 trillion gigabytes by 2020. The massive growth in data so called big data, emerges out with a lot of challenges. To name a few, managing the huge volume of data, analyzing it , storing and the visualizing data . Numerous big company partners comes out with various alternative solutions. Out of which, the most familiar framework that provides a good solution is the Hadoop Ecosystem. The word Ecosystem is coined as the framework is the combination of many components. The two most vital components in the Ecosystem are the hadoop distributed file system and the Map Reduce. The former is the storage part of hadoop and the later is the processing part. In this paper we strive hard to focus on the processing part of the hadoop. The Map reduce process need some technical experts to process Big Data. Apache Pig is one of the Hadoop component used to process Big Data in minimum time duration with less technical knowledge. In this paper an insight on Big Data analytics using pig script is made using Library data set. From the analytics the frequent library users, the books accessed frequently by the students, authors preferred routinely by the students, and most regular date and time of students are analyzed.