2015 chapter
Determining Query Readiness for Structured Data
In Big Data Analytics and Knowledge Discovery (pp. 3–14).
author keywords: Big data quality; Big data analytics and user interfaces; Data readiness level; Data quality measurement; Data quality improvement
TL;DR:
This study provides a formalization of DRL in a structured-data scenario, and illustrates how knowledge of rules and facts can be used to identify those transformations of the data that improve its DRL.
(via Semantic Scholar)
open access via www.lib.ncsu.edu (repository)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions
(OpenAlex)
Source: Crossref
Added: February 24, 2020
The outcomes and quality of organizational decisions depend on the characteristics of the data available for making the decisions and on the value of the data in the decision-making process. Toward enabling management of these aspects of data in analytics, we introduce and investigate Data Readiness Level (DRL), a quantitative measure of the value of a piece of data at a given point in a processing flow. Our DRL proposal is a multidimensional measure that takes into account the relevance, completeness, and utility of data with respect to a given analysis task. This study provides a formalization of DRL in a structured-data scenario, and illustrates how knowledge of rules and facts, both within and outside the given data, can be used to identify those transformations of the data that improve its DRL.