Results 301 to 310 of about 11,695,622 (343)
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Drug News & Perspectives, 1998
When collecting data, deciding what type and how much to obtain will depend in large measure on how the data will be used and the group(s) that will be given the data, as well as the risk-taking or risk-averse position adopted. Among the most important issues involving the quality of data are knowing what plans and activities will lead to obtaining ...
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When collecting data, deciding what type and how much to obtain will depend in large measure on how the data will be used and the group(s) that will be given the data, as well as the risk-taking or risk-averse position adopted. Among the most important issues involving the quality of data are knowing what plans and activities will lead to obtaining ...
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2017
This entry presents a definition of data and their quality dimensions as the basis for a survey of data quality management and improvement techniques, with special attention to data published on the Internet. Over the past several years several factors have contributed to making improved data quality an urgent priority.
Christopher J. Fox +2 more
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This entry presents a definition of data and their quality dimensions as the basis for a survey of data quality management and improvement techniques, with special attention to data published on the Internet. Over the past several years several factors have contributed to making improved data quality an urgent priority.
Christopher J. Fox +2 more
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2007
This chapter presents results from a large-scale survey of Australian CPA members regarding data quality. The research investigates and reports major stakeholders’ opinions on the importance of critical success factors affecting data quality and the actual performance on each of those factors. The results reveal whether dissimilarly sized organizations
Jeretta Horn Nord +3 more
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This chapter presents results from a large-scale survey of Australian CPA members regarding data quality. The research investigates and reports major stakeholders’ opinions on the importance of critical success factors affecting data quality and the actual performance on each of those factors. The results reveal whether dissimilarly sized organizations
Jeretta Horn Nord +3 more
openaire +1 more source
1996
There are serious obstacles to systematic studies of dream content. First, as noted in the first chapter, it is not possible to introduce stimuli that regularly produce predictable variability in dream content, so an experimental approach is not very useful.
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There are serious obstacles to systematic studies of dream content. First, as noted in the first chapter, it is not possible to introduce stimuli that regularly produce predictable variability in dream content, so an experimental approach is not very useful.
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Big Data Quality: A Data Quality Profiling Model
2019Big Data is becoming a standard data model, and it is gaining wide adoption in the digital universe. Estimating the Quality of Big Data is recognized to be essential for data management and data governance. To ensure a fast and efficient data quality assessment represented by its dimensions, we need to extend the data profiling model to incorporate ...
Ikbal Taleb +2 more
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Challenges to the quality of data-quality measures
Food Chemistry, 2009Demands are growing for information on the quality of food composition data. It is generally acknowledged today that the traditional measures of data quality (e.g. standard deviations) do not adequately address the complex issues affecting the quality of food composition data.
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Journal of the American Statistical Association, 1985
Abstract Commonly accepted hypotheses guide practical determination of needed data quality; for example, as the probability that a decision uses data increases, the needed data quality increases, and the more rudimentary the uses of the data, the less data quality is needed.
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Abstract Commonly accepted hypotheses guide practical determination of needed data quality; for example, as the probability that a decision uses data increases, the needed data quality increases, and the more rudimentary the uses of the data, the less data quality is needed.
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Data Quality in Data Warehouses
2005Fayyad and Uthursamy (2002) have stated that the majority of the work (representing months or years) in creating a data warehouse is in cleaning up duplicates and resolving other anomalies. This article provides an overview of two methods for improving quality. The first is data cleaning for finding duplicates within files or across files.
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