Semantic Recognition of a Data Structure in Big-Data

Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

1Laboratory LIPN-UMR 7030-CNRS, University Paris 13, Sorbonne Paris Cité, Villetaneuse, France 2Company Talend, Suresnes, France.
Company Talend, Suresnes, France.
Laboratory LIPN-UMR 7030-CNRS, University Paris 13, Sorbonne Paris Cité, Villetaneuse, France.

DOI: 10.4236/jcc.2014.29013                

Abstract

Data governance is a subject that is becoming increasingly important in business and government. In fact, good governance data allows improved interactions between employees of one or more organizations. Data quality represents a great challenge because the cost of non-quality can be very high. Therefore the use of data quality becomes an absolute necessity within an organization. To improve the data quality in a Big-Data source, our purpose, in this paper, is to add semantics to data and help user to recognize the Big-Data schema. The originality of this approach lies in the semantic aspect it offers. It detects issues in data and proposes a data schema by applying a semantic data profiling.

Keywords

Data Quality, Big-Data, Semantic Data Profiling, Data Dictionary, Regular Expressions, Ontology

Conflicts of Interest

The authors declare no conflicts of interest.

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