Open AccessFactors Affecting The Usability Of Unstructured Big Data
Author(s) -
Joshua Devadason,
Rehan Akbar
Publication year - 2020
Publication title -
jisr on computing/journal of independent studies and research computing
Language(s) - English
Resource type - Journals
eISSN - 2412-0448
pISSN - 1998-4154
DOI - 10.31645/09
Subject(s) - usability , unstructured data , big data , computer science , data science , identification (biology) , knowledge management , data mining , human–computer interaction , botany , biology
Big data is a valuable asset for organisation as it analyses and help to understand the customers, changes within their business environment, market analysis and future trends. The big data is multifaceted (different data types and versatile), and mostly exists in unstructured formats. The extraction of value from this data is challenging. The usability and productivity of this multifaceted unstructured data is greatly compromised. A number of factors and associated reasons affect the usability of unstructured big data. The present research work investigates these factors and associated reasons behind the usability issues of multifaceted unstructured big data. The identification of these factors contribute to develop solutions to reduce the lack of usability of highly unstructured big data. A detailed study of existing literature followed by survey questionnaire has been conducted to identify the factors and their reasons. Descriptive statistics has been used to analyse and interpret the data and results.