Application of Big Data Analytics in Agriculture
Hey guys, in this post we are going to explore application of big data analytics in agriculture industry.
Let us have an insight to the agriculture industry…….
From ancient time agriculture has been the backbone of Indian economy. In present era, agriculture sector requires application of technological revolutions happened in the last decade like IT services, IoT, AI, machine learning, cloud storage, big data analytics etc. India is a country of 1.36 billion population and 70% of population lives in the villages. Major population (approximately 40%) is dependent on the agricultural related activities. Agriculture sector is also fairly contributing to the GDP. But this sector in demand of technological adoption and implementation to make it profitable sector. The government of India also intends to make agricultural income double as soon as possible and it only possible with the help of disruptive technologies. Thus, a new need has emerged and across sectors, the use of data to inform decision-making is currently the accepted norm.
The agriculture has embraced mechanical advancement using efficient methods of ploughing farms, spraying, and harvesting etc that increased food grain production and made self-reliant to the nation. And now, it is high time to adopt and implement recent technological innovation in agriculture sector. Use of recent technological revolution like information technology, artificial intelligence, machine learning, big data analytics with internet of things etc can bring drastic positive change in the development of agriculture and can increase manifold profitability that would make agriculture a profitable profession. It will also attract to the well-educated and tech savvy citizens. Application of big data analytics in agriculture can make wonders.
Some decent applications of big data analytics / data science in agriculture are given below:
· Forecasting crop production and improving crop yields.
· Improve farming operations.
· Disease prediction and pesticide recommendation
· Analysis of soil heath and crops recommendation.
· Recommendation of quantity of fertilizers and pesticides
· Recommendation of profitable corps
· Attract greater investments in Agtech.
· Improve supply chain / Supply chain tracking.
· Weather prediction
· Risk assessment
· Food security
· Stop migration of the local labours.
· Reduce crop production cost.
· Efficient monitoring and management of crops etc.
Career opportunities in big data analytics / data science in Agriculture
The roles and responsibilities of a big data analyst / data scientist in agriculture is very similar to the other industries. In general, there are following tasks performed by the data scientist / big data analyst:
· Data collection / Data Capture
· Data Storage
· Data Transfer
· Data pre-processing
· Data Transformation
· Data modelling
· Perform Analytics (descriptive, diagnostic, predictive, and prescriptive)
· Data Marketing
· Predicting trends and recommendations.
· Data Visualization etc.
Farmers, agriculture industry and government are making efforts to make this industry self-reliant and profitable business. It is very evident that application of big data analytics in the agriculture industry is rapidly emerging. Thus, big data analytics professionals demand will increase manifold in coming time.
On winding up notes, feel free to share your feedback. See you in the next week.