Application of Big Data in Agriculture has great scope as Precision Agriculture is heavily dependent on data. Farm productivity can greatly improve through insights such as success rate of fertilizers in a particular terrain. Agriculture Data could be data about the success of a specific crop in a given geographical climate. Such information can be particularly of interest to farmers, Agricultural companies, and Agriculture consultants. However, information exchange is rather limited for all these parties due to the following problems: Many Farmers have limited knowledge of Agriculture Data and methodologies of farming. Due to this agricultural productivity remains limited. Consultants to guide Farmers regarding new technology and Agriculture Analytics are limited especially in remote areas. Agriculture Companies producing fertilizers and other agricultural products resort to physical testing before they launch the products. The results from such tests are not very reliable since the trials take place in a specific environment and do not take into account other types of geographical conditions. Business Solution At Gowitek we have developed a Mobile and Web-based data science Application that can solve the above problems by providing an Organized crop-planning and process management platform: 1. It enables farmers to analyze crop yield and health in real-time. With secure messaging channel between consultants and farmers, help is readily available to farmers, thereby reducing damage to the crops. 2. It also allows Consultants to reach out to as many farmers as possible. 3. 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: A. Agriculture industry regarding prospective success of products in different markets. B. Farmers about success of different crops, predictive impact of natural conditions, etc. To read more: https://www.gowitek.com/analytics/case-studies/big-data-in-agriculture