10th International Conference on the Quality of Information and Communications Technology, QUATIC 2016.[Excerpt] Recent studies have shown that poor quality data is predominant in many Big Data systems containing a variety of sources such as linked data, mobile data, social media data, Internet of Things data, and many others. The fourth "V" of big data (veracity) directly refers to uncertainty and data quality problems. With the variety of Big Data sources, new frameworks and methods are needed for quality assessment, management and improvement due to the sheer volume and velocity of data. Although significant progresses have been made, mainly in what concerns technologies for processing Big Data, several challenges still remain, including...
With a continuously increasing amount and complexity of data being produced and captured, traditiona...
The term "big data" has been characterized by challenges regarding data volume, velocity, variety an...
High-quality data is a prerequisite for most types of analysis. However, since data quality does not...
Big data has made its appearance in many fields, including scientific research, business, public adm...
Due to the importance of quality issues in Big Data, Big Data quality management has attracted signi...
This article investigates the evolution of data quality issues from traditional structured data mana...
In this paper, we discuss the application of concept of data quality to big data by highlighting how...
In the Big Data Era, data is one of the most important core elements for any governmental, instituti...
We constantly produce lots of data everyday via social media, public transport, global positioning s...
Although big data has become an integral part of businesses and society, there is still concern abou...
The increased reliance on data driven enterprise has seen an unprecedented investment in big data in...
Achieving high level of data quality is considered one of the most important assets for any small, m...
In the health industry, the use of data (including Big Data) is of growing importance. The term &lsq...
Lilli Braunisch, Malte Schweia, Peter Graeff & Nina Baur (2020) Forum of Historical Social Researc...
The Data Warehousing Institute (TDWI) estimates that data quality problems cost U.S. businesses more...
With a continuously increasing amount and complexity of data being produced and captured, traditiona...
The term "big data" has been characterized by challenges regarding data volume, velocity, variety an...
High-quality data is a prerequisite for most types of analysis. However, since data quality does not...
Big data has made its appearance in many fields, including scientific research, business, public adm...
Due to the importance of quality issues in Big Data, Big Data quality management has attracted signi...
This article investigates the evolution of data quality issues from traditional structured data mana...
In this paper, we discuss the application of concept of data quality to big data by highlighting how...
In the Big Data Era, data is one of the most important core elements for any governmental, instituti...
We constantly produce lots of data everyday via social media, public transport, global positioning s...
Although big data has become an integral part of businesses and society, there is still concern abou...
The increased reliance on data driven enterprise has seen an unprecedented investment in big data in...
Achieving high level of data quality is considered one of the most important assets for any small, m...
In the health industry, the use of data (including Big Data) is of growing importance. The term &lsq...
Lilli Braunisch, Malte Schweia, Peter Graeff & Nina Baur (2020) Forum of Historical Social Researc...
The Data Warehousing Institute (TDWI) estimates that data quality problems cost U.S. businesses more...
With a continuously increasing amount and complexity of data being produced and captured, traditiona...
The term "big data" has been characterized by challenges regarding data volume, velocity, variety an...
High-quality data is a prerequisite for most types of analysis. However, since data quality does not...