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Extract the Analyzed Information from Dark Data

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Extract the Analyzed Information from Dark Data

Rahul P | Ganeshan M

Rahul P | Ganeshan M "Extract the Analyzed Information from Dark Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4, June 2020, pp.26-29, URL: https://www.ijtsrd.com/papers/ijtsrd30842.pdf

The world is surrounded by data and data, the data may be structured, unstructured, or semi-structured; every organization generates enormous data daily, only the tip of data is analyzed, and the larger the data is ignored from the utilizable analysis. This paper focuses on a particularly unstructured and bothersome class of data, termed Dark data. Dark data is not attentively analyzed, indexed, and stored, so it becomes nearly imperceptible to potential users and therefore is more likely to last neutralized and eventually lost. This paper discusses how the concepts of long-term specifically use of analyzed for all intents and purposes dark data can be used to generally understand the very possible solutions for better curation of dark data in a major way. This paper describes why this class of data is so critical to scientific progress, some of the properties of this dark data, as well as the technical difficulties to useful management of this class of data. Many probable useful institutional and technical solutions are under development which will show in this paper in the last section, but these solutions are mainly conceptual and require additional research during lack of resources.

Dark Data; Big Data Analytics, Structured Data, Unstructured Data, and Semi-Structure Data

Volume-4 | Issue-4, June 2020
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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