BibTeX:

@article{IJIRSTV1I10084,
     title={Measure Customer Behaviour Using C4.5 Decision Tree Mapreduce Implementation in Big Data Analytics and Data Visualization},
     author={Sreena Gopinathan Nair, Nadeem Abdulla, Zubair Ahmed Mohammed Gazzali and Anindita Khade},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={10},
     pages={228--235},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I10084.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Even though there are lots of invented systems that have implemented customer analytics, it’s still an upcoming and unexplored market that has greater potential for better advancements. Big data is one of the most raising technology trends that have the capability for significantly changing the way business organizations use customer behaviour to analyze and transform it into valuable insights. Also decision trees can be used efficiently in the decision making analysis under uncertainty which provides a variety of essential results. Hence to the end of this paper, we propose the MapReduce implementation of well-known statistical classifier, C4.5 decision tree algorithm. The paper additionally mentions why C4.5 is preferred over ID3. Apart from this, our system aims to implement Customer data visualization using Data Driven Documents (d3.js) which allows you to build well customized graphics.

Big data analytics, C4.5 algorithm, D3.js, Data visualization, Decision tree, Hadoop, MapReduce