SHANLAX International Journal of Arts, Science and Humanities http://www.shanlaxjournals.in 7 Research Guidelines on Big Data and Data Analytics: A Survey B.Vaishnavi Research Student, Government Arts College, Thiruvannamalai, Tamil Nadu, India V.Uma Assistant Professor, Government Arts College, Thiruvannamalai, Tamil Nadu, India C.Sunitha Ram Assistant Professor, SCSVMV University Kanchipuram, Tamil Nadu, India Abstract Large number of devices and objects are now linked to the internet,to transmit data, and collect data back for analytics. The goal is here to utilize this data to make a positive impact on our lifestyle, energy conservation, transportation,and health. The term “Big Data” existed before IoT arrived to carry out the analytics. Themanagement of Big Data in a constantly expandingnetwork gives rise to non-trivial concerns regarding datacollection efficiency, data processing, analytics, and security. In this effort, thereforewe carry out a survey on Big Data technologies in different domains to make easy and inspire knowledge sharing across different fields. Based on the review, this work discussesanoverview, architecture, applications, challenges, techniques, methodologies, privacy and technologies, similarities and differences among Big Data technologies used in different domains, proposes how sure Big Data technology used in one realmcan be re-used in an additional area , and develops an abstract framework to outline the Big Data technologies. Then a structure may be established based on the emerging innovation behind data and analytics, managing, exploring and enabling the challenges in different task leads to the evolution of Big Data and Analytics. Keywords: Big Data, Big Data Analytics, Internet of Things. Introduction The term Big Data was coined under the explosive increase of global data and was mainly used to describe the enormous datasets. These datasets are compared with traditional datasets because it does not support real- time data [i.e.,15 unstructured data].Thisleads to the evolution of Big Data [1]. In January 2007, Jim Gray, a pioneer of database software, called such transformation “The Fourth Paradigm” [2]. He also thought the only way to cope with such a paradigm was to develop a new generation of computing tools to manage, visualize, and analyze massive data. In June 2011, another milestone event occurred, when EMC/IDC published a research report titled Extracting Values from Chaos [3], which introduced the concept and potential of Big Data. This research report aroused great interest in both industry and academia on Big Data. Big Data analytics [4] examines large amounts of data to uncover hidden patterns, correlations and other insights.Data-driven companies already using machine-generated data from the IoT to enhance customer service,generate moreyields from new products and services, optimize data and feed more data into existing analytical efforts. OPEN ACCESS Volume: 6 Issue: 3 Month: Januray Year: 2019 ISSN: 2321-788X Received: 01.11.2018 Accepted: 03.01.2019 Published: 30.01.2019 Citation: Vaishnavi, B., and C. Uma, V & Sunitha Ram. “Research Guidelines on Big Data and Data Analytics: A Survey.” Shanlax Internatioal Journal of Arts, Science and Humanities, vol. 6, no. 3, 2019, pp. 7–17. DOI: https://doi.org/10.5281/ zenodo.2550001