eFoodPrint Big Data & Business Intelligence in Agriculture
eFoodPrint Big Data and Business Intelligence is a new service aimed at the agricultural sector
eFoodPrint enters the world of Big Data thanks to a collaboration agreement with the Faculty of Economic and Social Sciences of UIC Barcelona, within the framework of the Executive Master in Big Data Science (MBDS), with the aim of studying initiatives related to the field of Machine Learning.
Through this agreement with UIC Barcelona, a team of professionals studying the Executive Master in Big Data Science, aims to provide a set of solutions to a series of needs in the agricultural sector, highlighting as challenges the predictions of harvest, the detection of degradation curves of phytosanitary products and pest prediction models.
HOW CAN BIG DATA CONTRIBUTE TO AGRICULTURE?
✔ Making decisions without data or adequate information can cause important losses in any business. Technology and models based on Big Data provide predictions to optimize decision making.
✔ Stock and Logistics: Buy or sell based on harvest predictions. Get ahead of your competitors and optimize the cold capabilities of your organization.
✔ Commercial and Financial Area: Facilitate harvests dates and more reliable production volumes to your customers. Improve the operating margin of your activity by anticipating the market.
✔ Human Resources: Anticipate the needs of field and warehouse personnel based on predictions of volume and harvest dates.
WHAT DO WE NEED TO APPLY BIG DATA IN AGRICULTURE?
✔ We use data from any ERP and in different formats such as excel and csv. We add meteorological data and other sources to obtain predictions for agriculture.
✔ Other sectors already use solutions based on predictive models that use Machine Learning applications that surpass human predictions. Why not in Agriculture?
REQUEST HERE MORE INFORMATION WE WILL SEND YOU A TEMPLATE TO KNOW IF YOUR ORGANIZATION CAN OBTAIN HARVEST PREDICTIONS
eFoodPrint BI allows you to extract agricultural information from different sources (such as ERP’s, Hesperides, eFoodPrint ENV, digital field notebooks … etc) and combine it to create personalized and dynamic reports of quality, technical and economic results.