DaQL 2.0: Measure Data Quality based on Entity Models

C. Lettner, R. Stumptner, W. Fragner, F. Rauchenzauner, L. Ehrlinger. DaQL 2.0: Measure Data Quality based on Entity Models. volume 180, pages 772-777, DOI 10.1016/j.procs.2021.01.327, 2, 2021.

Autoren
  • Christian Lettner
  • Reinhard Stumptner
  • Werner Fragner
  • Franz Rauchenzauner
  • Lisa Ehrlinger
BuchProcedia Computer Science
TypIn Konferenzband
Band180
DOI10.1016/j.procs.2021.01.327
Monat2
Jahr2021
Seiten772-777
Abstract

In order to make good decisions, the data used for decision-making needs to be of high quality. As the volume of data continually increases, ensuring high data quality is a big challenge nowadays and needs to be automated with tools. The goal of the Data Quality Library (DaQL) is to provide a tool to continuously ensure and measure data quality as proposed in [5]. In this paper, we present the current status of the development of the new DaQL version 2.0. The main contribution of DaQL 2.0 is the possibility to define data quality rules for complex data objects (called entities), which represent business objects. In contrast to existing tools, a user does not require detailed knowledge about the database schema that is observed.