In the present world, where more and more users upload data to the internet, the overall size of data that need to be stored and analyzed exceeds the capacity of traditional storage and analysis techniques. Hence, it is necessary to introduce new and efficient methods for the analysis of Big Data in order to extract useful information from them. Big Data has tremendous importance in almost all areas such as education, healthcare, etc. Big data is defined by its three main characteristics which are high volume, high velocity and huge variety. Hadoop is provides an efficient platform for the analysis of Big Data. It consists of a distributed storage system, HDFS for the storage of large volumes of data and a programming framework, MapReduce for the analysis of data.

1. Avita et al, "Big Data: Issues, Challenges, Tools and Good Practices," in IEEE Sixth International Conference on Contemporary Computing, 2013, pp. 404-409.
2. Raymond Gardiner Goss and KousikanVeeramuthu, "Heading Towards Big Data Building a Better Data Warehouse for more data, more speed and more users," in IEEE 24th Annual SEMI Advanced Semiconductor Manufacturing Conference, 2013, pp. 220-225.
3. Nader Mohamed and Jameela Al-Jaroodi, "Real-Time Big Data Analytics: Applications and Challenges," in IEEE International Conference on High Performance Computing and Simulation, 2014, pp. 305-310.
4. Tom White, "Meet Hadoop, " in Hadoop: The definitive guide, 3rd Edition, California: O'Reilly Media, 2012, ch. 1, pp. 9-15.
5. Jean Pierre Dijcks, "Oracle: Big Data for the Enterprise," in Oracle White Paper, 2013© Oracle Corporation.
6. Divyakant Agrawal et al. , "Challenges and Opportunities with Big Data," Cyber Center Technical Reports, Purdue e-Pubs, Purdue University, 2011.
7. Sonja Zillner et al, "Towards a Technology Roadmap Big Data Applications in the Healthcare Domain," in IEEE 15th International Conference on Information Reuse and Integration, California, 2014, pp. 291-296.
8. F. CananPembeMuhtaroglu et al, "Business Model Canvas Perspective on Big Data Applications," in IEEE International Conference on Big Data, 2013, pp. 32-37.
9. HimanshuRathod and Tarulata Chauhan, "A Survey on Big Data Analysis Techniques," in International Journal for Scientific Research and Development, 2013, vol, 1, issue. 9, pp. 1806-1808.
10. Bill Vorhies. (2013, October 13). How many "V"s in Big Data- The Characteristics that define Big data. [Online]. Available: http://data-magnum. com/how-many-vs-in-big-data-the-characteristics-that-define-big-data/
11. Steven Norton. (2014, July 10). Germany's 12th man at The World Cup: Big Data. [Online]. Available: http://blogs. wsj. com/cio/2014/07/10/germanys-12th-man-at-the-world-cup-big-data/
12. DhrubaBorthakur. (2013, April 8). HDFS Architecture Guide. [Online]. Available: https://hadoop. apache. org/docs/r1. 2. 1/hdfs_design. html
13. Ricky Ho. (2008, December 16). How Hadoop Map/Reduce works. [Online]. Available: http://architects. dzone. com/articles/how-hadoop-mapreduce-works
14. Craig Smith. (2015, March 19). By the Numbers: 200+Amazing Facebook User Statistics (February 2015). [Online]. Available: http://expandedramblings. com/index. php/by-the-numbers-17-amazing-facebook-stats
15. Hannes Venter, "Case Study Mauritius: Successful Implementation of Innovative Public Revenue Management Solutions," in IST- Africa Conference Proceedings, 2014.

Hdfs Mapreduce