• Dukitha.M
• Sangeetha .K
• Chaya.M

With the beginning of new period data has grown rapidly not only in size but also in variety. There is a complexity in analyzing such big data. Data mining is the technique in which useful information and unseen relationship among data is extracted. Clustering is one of the most important techniques used for data mining in which mining is performed by result out clusters having similar group of data. Broad analysis of these techniques is agreed out and proper clustering algorithm is provided. This paper focuses on a intense study of unlike clustering algorithms highlighting the characteristics of big data.

clustering techniques- Partitioning, Density, Grid Based, Model Based, Hierarchical.

"A STUDY AND ANALYSIS OF CLUSTERING TECHNIQUES FOR BIG DATA ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 9, page no.108-113, September 2019, Available :http://www.jetir.org/papers/JETIRDD06020.pdf

"A STUDY AND ANALYSIS OF CLUSTERING TECHNIQUES FOR BIG DATA ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 9, page no. pp108-113, September 2019, Available at : http://www.jetir.org/papers/JETIRDD06020.pdf