Data Analytics for Agriculture
                     Application of Big 
Data Analytics in 
Agriculture
Problem Statement
• Farmers have limited knowledge of 
current  technological advancements in 
agriculture, limiting production.
• Consultants to guide Farmers limited, in 
remote areas.
• Agricultural products are tried in a test 
environment ONLY, constraining usability.
Business 
Solution
A Mobile and Web-based IoT 
Application can solve the above 
problems by providing an Organized 
crop-planning and process 
management platform:
• It enables farmers to analyze crop 
health in real-time. With secure 
messaging channel between 
consultants and farmers, help is 
readily available to farmers, thereby 
reducing damage to the crops.
• It also allows Consultants to reach 
out to as many farmers as possible.
Business 
Solution
The Big data in Agriculture thus collected from 
such interactions regarding crops, weather, 
terrain, geographic conditions, water and more is 
stored and processed. This leads to the analytics 
part of our solution. By processing this data, the 
application will be able to assist:
• Agriculture companies regarding the 
prospective success of products in different 
markets
• Farmers about the success of various crops, 
the predictive impact of natural conditions, 
etc.
• Consultants will learn more about the most 
affected geographic areas where farmers 
could be assisted to deliver higher 
productivity.
Technology Solution
Such a Web Application server can be developed 
using Golang and an android application using 
React Native. Hadoop Platform stores Big Data and 
deep learning/Machine learning allow the platform 
to provide:
• Predictive Analytics: To predict the success of a 
product or crop or predict ill effects of a natural 
event on crops.
• Historical Data Analysis: Process vast volumes of 
historical data regarding crops, geography, etc.
• Real-Time Analytics: To provide Farmers with 
real-time assistance by analyzing information 
provided by them in real time.
Business 
Benefit
• Increased Agricultural Productivity 
through Agriculture Data
• Greater success of Fertilizing 
Products across a variety of 
geographic conditions for Agriculture 
Companies.
• Avoid ill effects of a particular 
natural occurrence.