This review considers the role of Big Data (BD), the digital revolution, the application of Internet of Things (loTs) and sensor technologies in the agriculture sector. The introduction is focussed on the ongoing research efforts on BD within agriculture sector, basic features of BD and latest development in BD analytics tools. In subsequent sections, the importance of BD applications in the agriculture sector and examples of their success stories in increasing farm productivity, current scenario on BD and digital agriculture, the future prospects of BD and bottlenecks in its implementation in agriculture sector are discussed. Agriculture sector is undergoing a new revolution and transformation, driven by IoT, sensor technologies, BD and cloud computing. This digital revolution in agriculture is very promising and will enable the agriculture sector to move to the next level of farm productivity and profitability. This transformation process looks irreversible and poised to revolutionize not only agriculture but the entire farm-to-food sector.
Motivation: Datafication-the growing presence, use and impact of data in social processes-is spreading to all sectors in developing countries. But, to date, there are few analyses of real-world experiences of datafication in developing country organizations. Purpose: We address this knowledge gap by analysing evidence of big data in practice in relation to three key issues: implementation, value and power. Approach and methods: Using interview, observation and documentary sources, we analyse the implementation and impact of big data systems in Indian electricity and transport public sector organizations. Findings: Big data systems have been much slower to implement than anticipated, and the article exposes the nature and scale of the implementation challenge facing such systems. These are already delivering value for some managers within public service organizations but are, as yet, more operational than strategic and incremental not transformative. Big data systems are facilitating a shift in power from the public sector to the private sector, and from labour and middle management to panopticon-type control by central managers. Big data intersects with politics especially around the imaginaries of wider stakeholders, changing their view of the financial and political issues that technology can address. Policy implications: Policy-makers and practitioners can better understand and plan for big data in development using three frameworks presented in the article: information value chain, decision pyramid, and big data-power model. These expose key issues of implementation, organizational value and power that must be incorporated into big data policy and projects. Benefits of datafication have been largely restricted to senior managers, private contractors and some politicians. To spread these to other stakeholders, including workers and citizens, action must be taken to address both practical and political issues arising in the datafication of development.
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