Loading

Challenges and Research Disputes and Tools in Big Data Analytics
K. Venkatesh1, M. Jafar Sathick Ali2, N. Nithiyanandam3, M. Rajesh4
1K.Venkatesh, Assistant Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai (Tamil Nadu), India.
2M.Jafar Sathick Ali, Assistant Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai (Tamil Nadu), India.
3N.Nithiyanandam, Assistant Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai (Tamil Nadu), India.
4M.Rajesh, Department of Computer Science and Engineering, KRS College of Engineering, India., RaGa Academic Solutions, Chennai (Tamil Nadu), India.
Manuscript received on 01 November 2019 | Revised Manuscript received on 13 November 2019 | Manuscript Published on 22 November 2019 | PP: 1949-1952 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F13760986S319/19©BEIESP | DOI: 10.35940/ijeat.F1376.0986S319
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Big Data is the era of data processing. Big Data is the Collate’s observer data sets that are complicated that traditional data-processing abilities. There are the various challenges include data analysis, capture the data, curation, search, sharing, stowage, transmission, visualization, and privacy violations. A large collections of petabytes of data is engendered day by day from the up-to-date information systems and digital era such as Internet of Things and cloud computing. Big data environs is used to attain, organize and analyse the numerous types of data. A large scale distributed file system which should be a fault tolerant, flexible and scalable. The term big data comes with the new challenges to input, process and output the data The technologies used by big data application to handle the massive data are Hadoop, Map Reduce, Pig, Apache Hive, No SQL and Spark. Initially, we extant the definition of big data and discuss big data challenges. Succeeding, The Propionate Paramour of Big Data Systems Models in the Into Prolonging Seam, Namely data Generation, data Assange, data Storage, and data Analytics. These four modules form a big data value chain. In accumulation, we present the prevalent Hadoop framework for addressing big data.
Keywords: Big Data, Hadoop, Map Reduce, Apache Hive, No SQL and Spark.
Scope of the Article: Big Data Analytics for Social Networking using IoT