Data quality management in the midmarket
Ready for the age of digitization?
As a result of its relevance for the development of new products, services or entire business models, the availability and use of data will also determine the future economic success of companies, according to a survey conducted by the digital association Bitkom in 2020.
There seems to be no shortage of data in this regard. To address the question of the value of data, the University of Lausanne, in collaboration with the Competence Center Corporate Data Quality (CC CDQ), has developed a data value formula. In addition to the volume of data, the factors of data quality and data usage play a decisive role in determining the value of data.The presentation starts with an overview of the basics for successful data quality management:
- What data exists in companies?
- What does data quality mean and how can it be measured?
- How can data quality management be embedded in the company?
In addition to the theoretical basics, Stephan Wund provides a practical insight into the methods of data profiling in the context of data quality management. For the automated derivation of business rules required for this purpose for the continuous and repeated measurement of data quality, he presents rule mining, a method from machine learning.
Stephan Wund will give the presentation at the 39th TDWI Roundtable in Frankfurt/Main.
|Event Date||2022-09-28 18:30|
|Event End Date||2022-09-28 19:45|