Flight Data Analysis Using PIG
Ishan Meena1, R. Aravind2, Vijayditya Sarker3, Nandhini4
1Ishan Meena, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Chennai (Tamil Nadu), India.
2R. Aravind, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Chennai (Tamil Nadu), India.
3Vijayditya Sarker, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Chennai (Tamil Nadu), India.
4Ms. Nandhini, Department of Computer Science and Engineering, SRM Institute of Science & Technology, Chennai (Tamil Nadu), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 727-732 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6248048419/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Precise prediction of passenger flow is very important for any company to create their business policies. The passenger analysis uses key technologies that is transmission of data dynamically, huge amount of data storage, fusing of data through multiple sources, data-mining and other analysis. With the use of visualisation, data prediction and decision making, the complete set of data (authorities, passengers) can create their own goals and perspectives. Therefore, the research provides both, accurate information about the transport services to common citizens and at the same time specify business models for lower tier and higher tier companies alike.
Keywords: PIG, Hadoop, Big Data, SQL
Scope of the Article: Predictive Analysis