Big data analytics: hadoop and tools
Mrunal Sogodekar, Shikha Pandey, Isha Tupkari, Amitkumar S. Manekar · 2016
Information technology gives utmost importance to processing of data. Some petabytes of data is not sufficient for storing large amount of data. Large volume of unstructured and structured data that gets created from various sources such as Emails, web logs, social media like Twitter, Facebook etc. The major obstacles with processing Big Data include capturing, storing, searching, sharing and analysis. Hadoop enables to explore complex data. It is an open source framework written in Java which supports parallel and distributed data processing and is used for reliable storage of data. With the help of big data analytics, many enterprises are able to improve customer retention, help with product development and gain competitive advantage, speed and reduce complexity. E-commerce companies study traffic on web sites or navigation patterns to determine probable views, interests and dislikes of a person or a group as a whole depending on the previous purchases. In this paper, we compare some typically used data analytic tools.