With the rise of big data, the quality of datasets has become a crucial factor affecting the
performance of machine learning models. High-quality datasets are essential for the …

Predictive analytics is transforming the maintenance and reliability of satellite
telecommunications infrastructure, offering proactive solutions to prevent downtime and …

The use of digital technologies for extracting information from various data sources can help
organisations to reduce uncertainty and improve decision‐making. The increasing …

The importance of meeting data quality standards in the context of Machine Learning (ML)
development pipelines is explored in this study. It delves deep into why good data is crucial …

Importance The lack of data quality frameworks to guide the development of artificial
intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in …

The fitness of the systems in which Machine Learning (ML) is used depends greatly on good-
quality data. Specifications on what makes a good-quality dataset have traditionally been …

While big data benefits are numerous, the use of big data requires, however, addressing
new challenges related to data processing, data security, and especially degradation of data …

This study answers research calls regarding data analytics in a specific unit and its impact at
the unit and organizational level. In doing so, it takes an information value chain approach to …

In light of its analytic capabilities, big data processing opens up additional opportunities.
Data comes from an assort-ment of sources, and the quick reception of digital technologies …

Since its emergence over two decades ago, process mining has flourished as a discipline,
with numerous contributions to its theory, widespread practical applications, and mature …