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Published in:
2015 | OriginalPaper | Chapter
Data Quality Issues in Data Migration
Authors : Nurhidayah Muhamad Zahari, Wan Ya Wan Hussin, Mohd Yunus Mohd Yussof, Fauzi Mohd Saman
Published in: Soft Computing in Data Science
Publisher: Springer Singapore
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The main criterion of a successful data migration project is the data quality. Quality of data can be compromised depending upon how the data are received, integrated, maintained, processed and loaded. The data migration project requires the data to be extracted from multiple sources before being cleansed and transformed. Once the data are cleansed and transformed, the data will be loaded into a new system. Therefore, data cleansing is the most important activity in a data migration project. Data cleansing is the process of detecting and removing errors, inconsistencies and redundancies in order to improve the quality of data