Big Data, the team that seldom rests
“Big Data is the best methodology for analyzing data and applying models that project a better future for farmers.” This is the conclusion that Luis Vargas, an agronomist with the International Maize and Wheat Improvement Center (CIMMYT), reached after participating in the workshop Analysis of Large Volumes of Commercial Data on Rice, which was held on 24-28 October at CIAT headquarters.
The objective of the event, organized by the Big Data team in CIAT´s Decision and Policy Analysis (DAPA) Research Area, was to strengthen the capacity of data mining technicians from various partner organizations in Latin America and the Caribbean, Their work centers on using models for analysis that converts data into information to facilitate decision making on farm.
“The group got a lot from the workshop. The participants quickly grasped the concepts and managed with ease the scripts provided by CIAT´s team. All of them were able to complete several rounds of analysis (dealing with climate, soils, and crop management), and this enabled them to make adjustments and see the importance of designing and choosing the variables with care,” said Sylvain Delerce, a specialist in site-specific agriculture with DAPA.
“Two teams – from Argentina´s National Institute of Agricultural Technology (INTA) and CIMMYT – succeeded in running the models directly from their own servers by means of remote connections (VPN). As a result, they were able to conduct the analysis more quickly and, most important – make the tool their own and reach the point of being able to repeat the procedure without assistance.”
Sylvain DelerceDuring the workshop, the CIAT Big Data team earned the name “the team that seldom rests,” because they are always organizing different types of events to share the capacities and new ways of thinking that agricultural professionals need.
“We´re a relatively young organization, requiring the guidance of experts who encourage us to seek out, collect, combine, analyze, visualize, and store large volumes of data to develop statistical reports and predictive models for soil management and climate change.”
Raúl GuerraArmando Taié, an agronomist with Argentina´s National Institute of Agricultural Technology (INTA), emphasized that what he most appreciated about the workshop was the collaborative work and the analysis carried out with the database on the CREA de Corrientes farmers group.
Involving participants from Mexico, Nicaragua, Argentina, and Colombia, the workshop offered a new opportunity to consolidate the community of practice on data mining in agriculture, in preparation for the launch next year of the CGIAR´s Big Data Platform, which CIAT will lead.
Workshop participants stressed the importance of adopting Big Data methodologies in organizations across Latin America and Africa, which is made possible with support from the World Bank and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
The authors from the post:
Sylvia María Pineda Ramos
Analista de comunicación interna del CIAT
Sylvain Delerce
Investigador de Big Bata y Agricultura Específica por Sitio (AEPS) del CIAT