Abstract
Data and information quality have been recognized as essential components for improving business efficiency. One approach for the assessment of information quality (IQ) is the manufacturing of information (MI). So far, research using this approach has considered a whole document as one indivisible block, which allows document evaluation only at a general level. However, the data inside the documents can be represented as components, which can further be classified according to content and composition. In this paper, we propose a novel model to explore the effectiveness of representing data as a composite unit, rather than indivisible blocks. The input data sufficiency and the relevance of the information output are evaluated in the example of analyzing an administrative form. We found that the new streamlined form proposed resulted in a 15% improvement in IQ. Additionally, we found the relationship between the data quantity and IQ was not a “simple” correlation, as IQ may increase without a corresponding increase in data quantity. We conclude that our study shows that the representation of data as a composite unit is a determining factor in IQ assessment.
Highlights
Data quality (DQ) and information quality (IQ) are recognized by business managers as key factors affecting the efficiency of their companies
The results suggest that this new representation of the data input should be considered in the evaluation of information quality output from a communication system (CS)
It is possible to capture the same information content with a smaller amount of data and produce a better quality of information; This new representation and model for evaluating data and information should help highlight the necessity of the consistent use of data and information terminology; This study shows that, for the already established attributes, a new classification should be considered, according to the moment when the analysis process is made; From the applicability of the Classification of Data (CD)-Processing Data into Information (PI)-A model, we found that the quality of information output can increase without necessarily having a corresponding increase in the quantity of data input
Summary
Data quality (DQ) and information quality (IQ) are recognized by business managers as key factors affecting the efficiency of their companies. The concept of quality for products has been defined as “fitness for use” [5,13,14,15,16,17]. For information products (IP), this definition applies only for “information quality” Information 2019, 10, 156 alone), because it depends on the perspective of the user. One piece of information could be relevant for one user and not relevant for another [16]. Data and information quality assessment should be evaluated according to required attributes for the business
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