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http://hdl.handle.net/11718/14051
Title: | Assessment and Prospects of Big Data Analytics in Public Policy in India |
Authors: | Kumar, Sachin Singh, Rampal Pal, Saibal K. |
Keywords: | Decentralization;Policy Implementation;Governance;Machine Learning;Diversity;Large data;Policy Features;IMLAPFF |
Issue Date: | 2015 |
Publisher: | Indian Institute of Management, Ahmedabad |
Citation: | Kumar, S., Singh, R., & Pal, S. K.. (2015). Assessment and Prospects of Big Data Analytics in Public Policy in India. 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. Indian Institute of Management, Ahmedabad |
Series/Report no.: | IC 15;074 |
Abstract: | Indian is emerging economy with potential to grow at double digit GDP growth rate. Sustainable growth and sustainable development require investment in technological innovations in governance product as well as governance processes. India is investing immensely to harness the full potential of resources. Incorporation of information and communication technology into governance process provides mainly two benefits. One is delivery of governance products and services in time bound, transparent manner with accountability. Second is collection of information from the actual consumer about products and services provided by the government. Second function plays a better role in improving effectiveness and efficiency of policy. India is country of great diversity with many traditions, cultures, food habits, environmental changes, flora and fauna, people perceptions and their employment habits. This poses challenges in front of the policy makers as to deal with vast amount of drivers information to analysis and formulate policy which is effectives and efficient in governance products delivery. This research paper discusses failures of policy making processes, reasons, problems with exiting systems, challenges posed by diversity and population in Indian context. This study first analysis the problems and challenges in policy domains at present and prospects of solution for solving them using machine learning and big data analysis by a proposing framework. This framework tries to improve the policy making cycle problems and provides better prospect for the future policy making by analyzing scenarios of the coming times. |
URI: | http://hdl.handle.net/11718/14051 |
Appears in Collections: | 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence |
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