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Data Quality Matrix: A Theoretical Perspective

Data Quality Matrix: A Theoretical Perspective
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Author(s): Prameela Singu (Mittal School of Business, Lovely Professional University, India) and Rayees Farooq (Indian Institute of Technology, Guwahati, India)
Copyright: 2020
Pages: 11
Source title: Handbook of Research on Connecting Research Methods for Information Science Research
Source Author(s)/Editor(s): Patrick Ngulube (University of South Africa, South Africa)
DOI: 10.4018/978-1-7998-1471-9.ch019

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Abstract

The objective of the study is to develop a data quality matrix, which can be used to measure the quality of data and response rate from respondents. The study is exploratory in nature, which applied the systematic review of literature extracted from different database. The study found that all the quadrants of the matrix (e.g., active, risky, and non-functional and deferential) have importance depending upon the nature of the study. The study further suggests that risky situation can be improved through enhancing the quality of data collected. The proposed matrix is very helpful in understanding the quantity and quality dimensions of the data in survey research. It helps to interpret survey results to fit between data representativeness and desired research outcomes.

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