Improving the Quality Validation of the ETL Process using Test Automation

被引：0

作者：

Staegemann, Daniel ^{[1
]}

Volk, Matthias ^{[1
]}

Jamous, Naoum ^{[1
]}

Venkatesh, Ranjan ^{[1
]}

Hart, Stefan Willi ^{[1
]}

Bosse, Sascha ^{[1
]}

Turowski, Klaus ^{[1
]}

机构：

[1] Otto von Guericke Univ, Magdeburg, Germany

来源：

AMCIS 2020 PROCEEDINGS | 2020年

关键词：

Big Data; Testing; Validation; ETL; Data Lake; Data Warehouse; Automation; BIG DATA; DESIGN; PERFORMANCE; SYSTEMS;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页数：10

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