Big Data is an essential research area for governments, institutions, and private agencies to
support their analytics decisions. Big Data refers to all about data, how it is collected …

Existing methodologies for identifying data quality problems are typically user-centric, where
data quality requirements are first determined in a top-down manner following well …

Enterprises are facing problems in managing the quality and value of their key data objects
(often referred to as master data). This article presents the findings from a case study …

To succeed in their business processes, organizations need data that not only attains
suitable levels of quality for the task at hand, but that can also be considered as usable for …

Timestamp information recorded in event logs plays a crucial role in uncovering meaningful
insights into business process performance and behaviour via Process Mining techniques …

In order to enhance their global business performance, organizations must be careful with
the quality of their information since it is one of their main assets. Analogies to quality …

Context: Data quality should be at the core of many Artificial Intelligence initiatives from the
very first moment in which data is required for a successful analysis. Measurement and …

The data preprocessing is an essential step in knowledge discovery projects. The experts
affirm that preprocessing tasks take between 50% to 70% of the total time of the knowledge …

Purpose: This article presents a maturity model for the evaluation of the information-driven
decision-making process (DMP) in small and medium enterprises. This model is called" …

Purpose The purpose of this paper is to develop data quality (DQ) assessment model based
on content analysis and metadata analysis. Design/methodology/approach A literature …