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Brous, Paul (author), Janssen, M.F.W.H.A. (author)Organizations are increasingly introducing data science initiatives to support decision-making. However, the decision outcomes of data science initiatives are not always used or adopted by decision-makers, often due to uncertainty about the quality of data input. It is, therefore, not surprising that organizations are increasingly turning to...journal article 2020
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Brous, P.A. (author), Janssen, M.F.W.H.A. (author), Krans, Rutger (author)More and more, asset management organizations are introducing data science initiatives to support predictive maintenance and anomaly detection. Asset management organizations are by nature data intensive to manage their assets like bridges, dykes, railways and roads. For this, they often implement data lakes using a variety of architectures...conference paper 2020
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Wahyudi, A. (author), Kuk, George (author), Janssen, M.F.W.H.A. (author)Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality....journal article 2018
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Wahyudi, A. (author), Farhani, Adiska (author), Janssen, M.F.W.H.A. (author)Today’s financial service organizations have a data deluge. A number of V’s are often used to characterize big data, whereas traditional data quality is characterized by a number of dimensions. Our objective is to investigate the complex relationship between big data and data quality. We do this by comparing the big data characteristics with...conference paper 2018