A Complete Research on Techniques & Technologies of Big Web Data Preparation to Web User Usage Behaviour
N. Silpa1, V. V. R. Maheswara Rao2

1N. Silpa, Research Scholar, Assistant Professor, Department of CSE, Centurion University of Technology and Management, Shri Vishnu Engineering College for Women Autonomous, Bhimavaram (Andhra Pradesh), India.
2Dr. V. V. R. Maheswara Rao, Professor, Department of CSE, Shri Vishnu Engineering College for Women Autonomous, Bhimavaram (Andhra Pradesh), India.
Manuscript received on 15 October 2019 | Revised Manuscript received on 24 October 2019 | Manuscript Published on 02 November 2019 | PP: 2356-2367 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B12690982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1269.0982S1119
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© 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: The rapid advancements in data digitization, the most powerful inventions of learning methodologies in data collection and reduced cost of data storage further enabled the World Wide Web with immense amount of data at significant rate in all the key domains. The generated web data is non-scalable, high dimensional, widely distributed, heterogeneous, dynamic in nature and having useful insights, and thus, it evolved as big data. This situation creates inevitably increasing opportunities in extracting structured solutions from unstructured weblog data for the present big data researchers. Moreover, to provide value addition to any key domain and derive actionable knowledge for various applications, such as, web usage analysis for improvements in fraud detection, product analysis and customer segmentation, got the focus in big data era by the web analysts. To improve operational performance and to discover hidden insights accurately, a comprehensive process is required to investigate the web user usage behavior by analyzing big web data. Towards this, the authors concentrate on reviewing the techniques and technologies of web data collection and preparation for investigating web user usage behavior effectively. In the present paper, the researchers initially pay an attention to explore web log data preparation methods in the traditional approach. Later, the review emphasizes on Hadoop approach for big data preparation and processing. This approach able to concentrate comprehensively on both the stages: distributed data storage and parallel processing of weblog data and to leverage the strengths of techniques and technologies of individual stages. Moreover, the authors deliberately review the possible potential research paths that results in an improved methodologies for data storage and optimized processing speed in the era of big web data.
Keywords: Big Data Analytics, Web Data, Hadoop, HDFS, MapReduce, Web Analytics, Web User Behavior, Web Data Preparation.
Scope of the Article: Web Mining