2015•Unpublished venueRequires access

Unravelling unstructured data: A wealth of information in big data

Mona Tanwar, Reena Duggal, Sunil Kumar Khatri

Open publisher page 46 citations

Abstract

Big Data is data of high volume and high variety being produced or generated at high velocity which cannot be stored, managed, processed or analyzed using the existing traditional software tools, techniques and architectures. With big data many challenges such as scale, heterogeneity, speed and privacy are associated but there are opportunities as well. Potential information is locked in big data which if properly leveraged will make a huge difference to business. With the help of big data analytics, meaningful insights can be extracted from big data which is heterogeneous in nature comprising of structured, unstructured and semi-structured content. One prime challenge in big data analytics is that nearly 95% data is unstructured. This paper describes what big data and big data analytics is. A review of different techniques and approaches to analyze unstructured data is given. This paper emphasizes the importance of analysis of unstructured data along with structured data in business to extract holistic insights. The need for appropriate and efficient analytical methods for knowledge discovery from huge volumes of heterogeneous data in unstructured formats has been highlighted.

About this research paper

What this paper is about

Big Data is data of high volume and high variety being produced or generated at high velocity which cannot be stored, managed, processed or analyzed using the existing traditional software tools, techniques and architectures. With big data many challenges such as scale, heterogeneity, speed and privacy are associated but there are opportunities as well. Potential information is locked in big data which if properly leveraged will make a huge difference to business. With the help of big data analytics, meaningful insights can be extracted from big data which is heterogeneous in nature comprising of structured, unstructured and semi-structured content. One prime challenge in big data analytics is that nearly 95% data is unstructured. This paper describes what big data and big data analytics is. A review of different techniques and approaches to analyze unstructured data is given. This paper emphasizes the importance of analysis of unstructured data along with structured data in business to extract holistic insights. The need for appropriate and efficient analytical methods for knowledge discovery from huge volumes of heterogeneous data in unstructured formats has been highlighted.

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OpenAlex reports 46 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Big Data is data of high volume and high variety being produced or generated at high velocity which cannot be stored, managed, processed or analyzed using the existing traditional software tools, techniques and architectures. With big data many challenges such as scale, heterogeneity, speed and privacy are associated but there are opportunities as well. Potential information is locked in big data which if properly leveraged will make a huge difference to business. With the help of big data analytics, meaningful insights can be extracted from big data which is heterogeneous in nature comprising of structured, unstructured and semi-structured content. One prime challenge in big data analytics is that nearly 95% data is unstructured. This paper describes what big data and big data analytics is. A review of different techniques and approaches to analyze unstructured data is given. This paper emphasizes the importance of analysis of unstructured data along with structured data in business to extract holistic insights. The need for appropriate and efficient analytical methods for knowledge discovery from huge volumes of heterogeneous data in unstructured formats has been highlighted.

Key concepts: Big data, Unstructured data, Data science, Computer science, Variety (cybernetics), Analytics, Data analysis, Knowledge extraction

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