Environmental Data Analytics for Empirical Values on Environmental Issues
M. Naveen Babu1, A.V. Krishna Prasad2
1M. Naveen Babu, Research Scholar, Department of CSE, KL (Deemed to be) University, Vijayawada, A.P, India.
2A.V. Krishna Prasad, Research Supervisor, Department of CSE, KL (Deemed to be) University, Vijayawada, A.P, India.
Manuscript received on 05 April 2019 | Revised Manuscript received on 10 May 2019 | Manuscript published on 30 May 2019 | PP: 1891-1898 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1355058119/19©BEIESP
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© 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: In the contemporary era, big data is highly regarded as the driver to promote productivity, efficiency and innovation. Emergence of big data and data science paved way for comprehensive analysis of data for obtaining business intelligence. Big data analytics has become crucial for enterprises to garner accurate knowhow for making well informed decisions. The cloud-big data ecosystem has been realized and thus it became easier to deal with big data and it’s processing as the storage and processing are outsourced to cloud. Different cloud computing platforms like Amazon AWS, Google cloud and Microsoft Azure made it a reality to work with big data which provides comprehensive understanding of data. With big data, environmental issues especially air pollution measurement and prediction can add value to existing infrastructure so as to improve the quality of prediction and also help in making strategic decisions. This paper represents the present state of the art on usage of big data analytics for adding value to different industries focusing more on environmental issues. It also provides the empirical values made with Apache Flink and Apache Spark for handling environment data. The preliminary results revealed that these frameworks play crucial role in processing big data.
Keywords: Big Data, Big Data Analytics, Environmental Issues, Apache Flink, Apache Spark
Scope of the Article: Big Data Analytics