The term data quality refers to measuring the fitness of data regarding the intended usage.
Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could …

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 …

Defining and evaluating data quality can be a complex task as it varies depending on the
specific purpose for which the data is intended. To effectively assess data quality, it is …

In recent years, as more and more data sources have become available and the volumes of
data potentially accessible have increased, the assessment of data quality has taken a …

The importance of context in data quality (DQ) was shown many years ago and nowadays is
widely accepted. Early approaches and surveys defined DQ as fitness for use and showed …

A known challenge related to big data is that data ingestion occurs continuously and at high
speed, and the data profile can quickly vary because of this dynamism. Data profiling can …

The widespread adoption of big data has ushered in a new era of data-driven decision-
making, transforming numerous industries and sectors. However, the efficacy of these …

Data Quality is one of the main challenges in any type of Big Data System. Timeliness is one
of the main factors in real-time Big Data. Limiting data quality evaluations to data sources …

In the last decade, we have been witnesses of the considerable increment of projects based
on big data applications and the evident growing interest in implementing these kind of …

In today's modern society, data play an integral role in the development global industry,
since they have become a valuable asset for companies, institutions, governments, and …