Trending Big Data Tools for Industrial Data Analytics

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Author(s): A. Bazila Banu (Bannari Amman Institute of Technology, India)and V. S. Nivedita (Bannari Amman Institute of Technology, India)
Copyright: 2023
Pages: 21
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch032

Keywords: Data Analysis and Statistics / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Big data is a substantial amount of data sets that cannot be stored, managed, or examined using conventional tools. Today, there are billions of data resources that generate data at a very speedy rate. These data resources are available across the world. Consider Facebook as an example—it produces 500 terabytes of data approximately every day which contains photographs, videos, text messages, emoticons, and more. In general, data that exists in the real world can be classified into different formats, like structured, semi-structured, and unstructured data. Structured data referred to as quantitative data has a well-defined format with only text /numbers which can be easily stored in the relational database. For example, data is represented in an Excel sheet. Semi-structured data has a partial format which may include tags. HTML tags fall in this category and need to be processed to store in the relational database. Unstructured data is otherwise referred to as qualitative data. For example, emails and video fall into this category.

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