Authors:
Timon Klann
1
;
Marcel Altendeitering
2
and
Falk Howar
1
Affiliations:
1
TU Dortmund University, Dortmund, Germany
;
2
Fraunhofer ISST, Dortmund, Germany
Keyword(s):
Data Quality Rules, Data Validation, Data Management, Domain Specific Language, Visual Programming.
Abstract:
High-quality data sets are vital for organizations as they promote business innovation and the creation of data-driven products and services. Data quality rules are a common approach to assess and enforce compliance with business domain knowledge and ensure the correctness of data sets. These data sets are usually subject to numerous data quality rules to allow for varying requirements and represent the needs of different stakeholders. However, established data quality tools have a rather technical user interface and lack support for inexperienced users, thus hindering them from specifying their data quality requirements. In this study, we present a tool for the user-friendly and collaborative development of data quality rules. Conceptually, our tool realizes a domain-specific language, which enables the graphical creation of rules using common data quality constraints. For implementation, we relied on CINCO, a tool for creating domain-specific visual modeling solutions, and Great Ex
pectations, an open-source data validation framework. The evaluation of our prototype was two-fold, comprising expert interviews and a focus group discussion. Overall, our solution was well-received and can contribute to lowering the accessibility of data quality tools.
(More)