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Paper Type
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Abstract
Due to the growing amount of data that are produced, the concept of big data analytics gained plenty of interest among researchers and practitioners. However, there are many challenges related to its use. One of those is the data storing and subsequently the corresponding extraction of required data. Since this process is prone to error, it requires thorough quality validation. To facilitate this procedure, an automated approach is proposed, using the example of a financial institution, replacing its formerly applied manual method. As a result, the time needed for a complete factory acceptance test could be reduced by 39 percent.
Recommended Citation
Staegemann, Daniel; Volk, Matthias; Jamous, Naoum; Venkatesh, Ranjan; Hart, Stefan Willi; Bosse, Sascha; and Turowski, Klaus, "Improving the Quality Validation of the ETL Process using Test Automation" (2020). AMCIS 2020 Proceedings. 11.
https://aisel.aisnet.org/amcis2020/strategic_uses_it/strategic_uses_it/11
Improving the Quality Validation of the ETL Process using Test Automation
Due to the growing amount of data that are produced, the concept of big data analytics gained plenty of interest among researchers and practitioners. However, there are many challenges related to its use. One of those is the data storing and subsequently the corresponding extraction of required data. Since this process is prone to error, it requires thorough quality validation. To facilitate this procedure, an automated approach is proposed, using the example of a financial institution, replacing its formerly applied manual method. As a result, the time needed for a complete factory acceptance test could be reduced by 39 percent.
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