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Data-Driven Decision Making For Indian Agriculture

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Udit Poddar, Data Scientist at SocialCops, gave this presentation on " Data-Driven Decision Making in Indian Agriculture: the Present and the Future" at the Fifth Elephant, 2016

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Data-Driven Decision Making For Indian Agriculture

  1. 1. AGRICULTURE IN INDIA Udit Poddar
  2. 2. THE PROBLEMS IN AGRICULTURE IN INDIA
  3. 3. • High Rice and Wheat Production • Extremely High Maternal Mortality, Infant Mortality Rates • High Malnutrition
  4. 4. Of India’s population is under-nourished 15% 194.6 million
  5. 5. India has a Pulse Problem Agriculture production trends in India (million tonnes) Rice Wheat Pulses
  6. 6. Irrigation availability High yielding disease resistant seeds Crop rotation literacy Accessibility to markets Pulses need more water Pulses are more susceptible to diseases Training & educating farmers Showcase the market to farmers What can fix it?
  7. 7. HOW DO YOU SOLVE THESE PROBLEMS USING DATA?
  8. 8. 1.26 bn 36 States & UTs 677 Districts 6000+ Sub-districs 6 lac+ Villages INDIA IS A COMPLEX COUNTRY
  9. 9. & IS EXTREMELY DATA RICH OPEN PUBLIC DATA
  10. 10. Number of land holdings Size of land holdings Dispersal of operated area Tenancy Status Sources of irrigation Irrigation status Cropping Intensity Crops Data Acquisition Data lying in government servers Agriculture Census Data and challenges Data Curation Single file for each geography and crop
  11. 11. Input Survey Data and challenges Data Acquisition Data lying in difficult government servers Data Curation Single file for each geography and crop
  12. 12. Challenges and Solutions Data Curation Available in PDF files or poorly formatted multiple Excel files • India’s population to cross China’s by 2022 • Population to grow up to 1.7b by 2050 • PDF parsing using image recognition • Data cleaning using pattern recognition • Scalable scripts for automating thousands of filesIntegrated Village wise Reports of disease outbreak in India Bi-weekly
  13. 13. Challenges and Solutions • India’s population to cross China’s by 2022 • Population to grow up to 1.7b by 2050 Data Stitching • Phonetic Matching • Fuzzy Logic Matches 15% The match we got the first time we matched Census Village Names to DISE Village Names
  14. 14. 15 209 Final Indicators Data Sources. 31 2k+ variables
  15. 15. • India’s population to cross China’s by 2022 • Population to grow up to 1.7b by 2050
  16. 16. • India’s population to cross China’s by 2022 • Population to grow up to 1.7b by 2050
  17. 17. THANK YOU

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