Impacts of climatic change on aquatic insects and their habitats: A global perspective with particular reference to India

Abstract :

Big Data Analysis is becoming very popular which has been implemented on many software development projects, and statisticians and data analysts are working alongside developers, testers and program managers. The design and development of data software systems that generate, collect, store, process, analyze, query, and visualize large sets of data is a significant challenges for both technical and social. Because data science is still an emerging discipline in software projects, there are many opportunities where software engineering researchers can help improve practice. In this paper, we share our experience working in this design space and describe the choices we made in tackling these challenges and their attendant trade-offs. We highlight the lack of developer support tools for data-intensive systems, the importance of multidisciplinary teams, the use of highly-iterative life cycles, the need for deep understanding of the frameworks and technologies used in data intensive systems, how simple operations transform into significant challenges at scale, and the paramount significance of data modelling in producing systems that are scalable, robust, and efficient.