Abstract—Data can take various forms and types such as numbers, symbols, words, images, and graphics. All these data are significant resources in companies’ operating process. So, if data has any quality problems (e.g. poor schema design, data entry errors, misspelling, inconsistency, and etc.), it will very risky for companies. On the other hand, high quality data can increase opportunities dependent on performance issues. This study introduces an automation tool enabling data quality tests of data warehouse applications. Also with this tool, historical changes of a dataset are analyzed with linear regression algorithm and, thus, outlier variables of data trend are reported to application users. The efficiency of the proposed automation tool is also tested and results are evaluated.

Index Terms—Data quality, data integrity, test automation, data warehouse, data statistics, data filtering.

Süleyman Eken and Ahmet Sayar are with Kocaeli University, Department of Computer Engineering, Kocaeli, Turkey (e-mail: suleyman.eken@kocaeli.edu.tr; ahmet.sayar@kocaeli.edu.tr).
Kürşat Topçuoğlu is with Turkcell Technology R&D, Kocaeli, Turkey (e-mail: kursattopcuoglu@gmail.com).

Cite:Süleyman Eken, Ahmet Sayar, and Kürşat Topçuoğlu, "AutoTest: Automation to Test Tabular Data Quality," International Journal of Computer and Electrical Engineering vol. 6, no. 4, pp. 365-368, 2014.