Big data integration

This solution was shared by PRE-LAUNCH RESEARCH TEAM , 14 May 2021

Print date: 04 October 2022 20:20

Description of the innovative solution

Big data Mobile phones Online services Precision agriculture Sensors Agricultural development Agricultural extension

The integration of big data (for example, genetic and environmental/climatic data) can optimise agriculture. Big data entails the collection, storage and processing of large amounts of data, often in real time. Big data can be multi-source (e.g. images, videos, remote sensing data), multi-temporal (e.g. collected at different points in time), and multi-resolution (e.g. have variable spatial resolution). Big data is most useful when it is high quality, which means it is relevant, accurate and reliable, produced in a timely fashion, coherent, and accessible. Big data can be used to provide predictive insights in farming operations, improve decision making and farm extension services, drive real-time operational decisions, and redesign business processes for game-changing business models.

Supply chain segment

Agricultural inputs and primary production practices

Maturity level

Moving to scale


Food safety Soil health Reducing biodiversity loss Increasing agrobiodiversity Reducing pollution

SDG target

SDG 2: Zero Hunger SDG 3: Good Health and Well-being SDG 12: Responsible Consumption and Production SDG 14: Life Below Water SDG 15: Life on Land


Urban Peri-urban Rural Marine/Coastal

Examples and additional resources

Real-world examples

See this solution in action in different contexts and settings around the world

Additional resources

Learn more about this solution through studies, articles, business cases, and other information

Implementing Big Data in Agriculture
News article, popular press or blog post
Blog post highlighting specific areas in agriculture where big data integration could transform efficiency.
Shared by IFSS Research Team


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