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Solve a problem of hunger: increase crops output by using technology of Business Intelligence

Updated on July 5, 2016

John Deere is one of biggest American corporation that manufactures agricultural products and machines. John Deere’s initiative is utilizing Business Intelligence and Big Data to help farmers increasing productivity. In return, this will increase farmers’ stickiness to the company, increase John Deere’s market share and help to accomplish the company’s vision to enrich human lives on the planet.
According to United National Food and Agriculture Organization, food production must be increased by 60% to feed the growing population that’s expected to hit 9 billion in 2050. To achieve this ambitious goal farmers and manufacturer should collaborate together by utilizing technology. In 2012, John Deere released several products that can connect its equipment with each other as well as to owners, operators, dealers and agricultural consultant. This interconnectivity will help farmers to achieve better results and efficiency. John Deere uses sensors connected to their equipment to collect information to help farmers manage their fleets and reduce the downtime for their tractors as well as save fuel. In addition to that, these historical and real-time data combined with weather forecast, soil conditions and crop features will help to increase crops productivity as well as increasing farmers’ revenue. Using BI with the generated data can maximize the outcome of the initiative. This required John Deere to develop an ETL process, dimensional model to address questions that help to increase farm productivity, BI tools to help in decision making process and covering governance & security concerns relating to storing and using data.
There is no shortage of data in the field of agriculture. With the new concept of precision agriculture real time data about weather, soil, elevation, air quality, crop maturity and varying seeds density in the field could be gathered using sensors placed through the field or connected to the agriculture machines, In some special cases, pictures of the fields took using satellites and robotic drones. The data gathered from the field transmitted over Wi-Fi network to data center that handle the process of transforming, aggregating and loading data for further analysis. In the case of John Deere, the data extracted from sensors. This row data contains detailed measurement of current field state such as soil profile, temperature and chemical properties. The data collected periodically and stored in data centers for later transformation process. The transformation process occurs in which data from previous extraction process combined together for each location in the field and loaded to the data warehouse.
During transformation process,

  • Different types of sensors from different vendors measure same characteristic in different unit so a unification process is required before loading data to warehouse.
  • Invalid measured data due to sensor failure should be discarded during transformation process.


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