• S.P.Victor
• D.Angeline Benitta

Big data generally focuses on analysis based consolidated approach with the expectation of desired results in a standard way of responses. The role of critical data is very effective when used in relation to a big data dealing with specific clusters. Big data in business organizations are entitled with specific field surroundings which are able to make twist and turns based on the value it occurs or on the frequency it changes often. The process of identifying the critical data is the lead to identify the characteristics that affect the business organizations, in order to improve the process the critical data identification and reasons for the change cause along with the current impact predictions are essential to improve the monitoring process in an organization. This proposed method of consolidation approach allowing only the most relevant information being provided to yield a higher quality of critical data results. This paper deals with the consolidation approach for providing a critical data identification with its effects in terms of its roles towards Big data indirectly for its security. In near future the focus will be to implement the neuro fuzzy approaches in real time using neural network conceptual schema for Big data security.

Big data, critical data, cluster, consolidation, optimality

"Consolidation Approach for Critical data Identification in Optimal Clusters towards Big Data Security", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 2, page no.167-176, February-2020, Available :http://www.jetir.org/papers/JETIR2002226.pdf

"Consolidation Approach for Critical data Identification in Optimal Clusters towards Big Data Security", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 2, page no. pp167-176, February-2020, Available at : http://www.jetir.org/papers/JETIR2002226.pdf