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Title:
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IDQMS: AN INTELLIGENT DATA QUALITY MANAGEMENT SYSTEM TOOL |
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Author(s):
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Aïcha Ben Salem and Faouzi Boufares |
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ISBN:
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978-989-8533-95-1 |
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Editors:
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Hans Weghorn |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Data Quality, Semantic Data Categorization, Semantic Dependencies, Data Cleaning |
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Type:
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Full Paper |
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First Page:
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3 |
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Last Page:
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10 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Today, the quantity of data continues to increase; furthermore, the data are distributed and heterogeneous, from multiple
sources (structured, semi-structured and unstructured) and with different levels of quality. Therefore, it is very likely to
manipulate data without knowledge about their structures and their semantics. The subject covered in this paper aims at
assisting the user in its quality approach. The data must be related to its semantic meaning, data types, constraints,
comments and origin. We deal with the semantic schema recognition of a data source. It consists of categorizing the data
by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and
possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better
understanding of the source and the alternatives for correcting data. |
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