The census is the source of information about demography, literacy, education, fertility and mortality, religions etc. This treasure of information is beneficial for the government and planning commission. This overall combined census data is high dimensional and unstructured, so it can be classified as big data and the application of analysis of big data for the purpose of extracting patterns in several research fields is now a worldwide problem. Since education is pathway to any nation building enterprises, it created enlighten society, meritocratic human resources, democratic society etc. So, by considering key role of education in development socioeconomic growth, education attainment of Maharashtra state is considered for the study purpose. The districts of Maharashtra state with similar education levels are clustered using cluster analysis. The ST category showed higher variation in literacy as compared to other categories.

1. Brian S. Everitt, Sabine Landau, Morven Leese, Daniel Stahl 2011. Cluster analysis, John Wiley and Sons, Ltd, 5th edition.
2. Bharti Thakur, Manish Mann 2014. Data Mining for Big Data: A Review, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 5.
3. Gouda Sateesh M, Sekher T. V. 2014. Factors Leading to School Dropouts in India: An Analysis of National Family Health Survey-3 Data. Journal of Research & Method in Education, Volume 4, Issue 6, PP 75-83.
4. Mamatha M. and Rao Nageswara V. 2015. Factors Influencing the Educational Attainment in India. International Journal of Mathematical Sciences, Technology and Humanities, Vol. 5, Issue 1, PP. 26-32.
5. Panicker Remya 2013. Adoption of Big Data Technology for the Development of Developing Countries. Proceedings of National Conference on New Horizons in IT – NCNHIT, ISBN 978-93-82338-79-6.
6. Panicker Remya 2016. Digitizing Indian Census Data for Analytics, Using Big Data Technology. International Journal of Advanced Research in Science, Engineering and Technology Vol. 3, Issue 3.
7. Patil R. D. , Jadhav Omprakash S. 2016. Some Contribution of Statistical Techniques in Big Data: A Review. International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 4, Issue 4, PP: 293 – 303.
8. Shariff Abusaleh, 1995. Socioeconomic and Demographic Differentials between Hindus and Muslims in India. Economic and Political Weekly.
9. Sujatha Sai D. , Reddy Brahmananda G. 2009. Women's Education, Autonomy and Fertility Behavior. Asia –Pacific Journal of the Social Sciences, Vol. I, PP: 35-50.
10. www. census. gov. in
11. https://en. wikipedia. org/wiki/Factor_analysis
12. www. cbs. gov. il/census
13. https://en. wikipedia. org/wiki/2011_Census_of_India

Big Data Data Analysis Chi-square Test Cluster Analysis Factor Analysis.