A small amount of data is very easy to manage as it can be straightforwardly saved in Dropbox or pen drives or many other devices. But when the data gets big as it is already getting with over 2.5 quintillion bytes created every day, data storage and analysis has become a great challenge. So as to manage and have access to the data without facing any hassles, the experts are of the opinion that Cloud Computing would be a solution for Big Data Problems.
Dr. A. K. Mishra, Senior Scientist at Indian Agricultural Research Institute addressed the gathering about ‘Big Data and Cloud Computing in Agri-Bioinformatics’ in the plenary talk session at 103rd Indian Science Congress at the University of Mysore.
Dr. Mishra said, “Cloud computing poses problems for developers and users of cloud software as it requires large data transfers over precious low-bandwidth. This also raises new privacy and security issues. However, it is an increasingly valuable tool for processing large datasets and it is already used by the US federal government, pharmaceutical companies, internet companies, scientific labs and bioinformatics services.”
On the same day, Dr. Binay Panda spoke on ‘Big Data and Personalized Medicine : Challenges and Opportunities for India’, Dr. Dinesh Gupta spoke on ‘Big Data Analysis in Biotechnology : Applications of Machine Learning and challenges towards clinical applications’ and Dr. Michael Gromiha on ‘Algorithms and Applications of Bioinformatics in Big Data analysis’. Prof. T Madhan Mohan chaired the programme.
Benefits of Cloud Computing
The very first reason is that that it helps in Big data analytics due to its application sharing and cost effective properties. This technology will help in current genomics data storage and analysis.
With respect to agriculture including plants and animals, it will be beneficial in sustainable livelihood and development. This has been proved with respect to the analysis that 90% of the data in the world today has been created in the last two years alone.
Cloud is a good option as hundreds of agricultural institutions across the country could be connected. Development of user-friendly crop computational algorithms and tools is needed.