Data Quality
Value-oriented measurement, management and improvement of data quality
Research team
Prof. Dr. Mathias Klier
Andreas Obermeier
Torben Widmann
Harnessing data treasures in businesses
In today's age of digitisation, organisations have access to very extensive and ever-growing quantities of data (keyword 'Big Data'). However, empirical evidence shows that the data that are being analysed and used are often of low data quality – even in internal customer databases, an average of around 30% of the stored data values are incorrect. Consequently, the average U.S. company, for example, incurs $15 million in additional costs annually. However, poor data quality is not only a major problem in companies – in times of fake news, politics and society have an increased need for reliable information. This is why quantitative methods are needed to measure, manage and improve data quality.
#data quality #fake news
Projects