Abstract: Independent from the concrete definition of the term “data qual-ity ” consistency always plays a major role. There are two main points when dealing with the data quality of a database: Firstly, the data quality has to be measured, and secondly, if is necessary, it must be improved. A classifier can be used for both purposes regarding consistency demands by calculating the distance of the classified value to the stored value for measuring and using the classified value for correction
Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment m...
We are living in a world of information abundance, surplus, and access. We have technologies to acqu...
Data collecting is necessary to some organizations such as nuclear power plants and earthquake burea...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
International audienceOne challenging aspects of data quality modeling and management is to provide ...
Data are important for making decisions. However, the quality of the data affects the quality of dec...
International audienceAs data types and data structures change to keep up with evolving technologies...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Data quality (DQ) assessment and improvement in larger information systems would often not be feasib...
Data quality is a central issue for many information-oriented organizations. Recent advances in the ...
Advanced analytical techniques such as data mining, text mining or predictive analytics are concepts...
Data Quality is, in essence, understood as the degree to which the data of interest satisfies the re...
Nowadays, activities and decisions making in an organization is based on data and information obtain...
In this paper we present research in progress that has the aim of developing a set of data quality m...
Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment m...
We are living in a world of information abundance, surplus, and access. We have technologies to acqu...
Data collecting is necessary to some organizations such as nuclear power plants and earthquake burea...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
International audienceOne challenging aspects of data quality modeling and management is to provide ...
Data are important for making decisions. However, the quality of the data affects the quality of dec...
International audienceAs data types and data structures change to keep up with evolving technologies...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Data quality (DQ) assessment and improvement in larger information systems would often not be feasib...
Data quality is a central issue for many information-oriented organizations. Recent advances in the ...
Advanced analytical techniques such as data mining, text mining or predictive analytics are concepts...
Data Quality is, in essence, understood as the degree to which the data of interest satisfies the re...
Nowadays, activities and decisions making in an organization is based on data and information obtain...
In this paper we present research in progress that has the aim of developing a set of data quality m...
Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment m...
We are living in a world of information abundance, surplus, and access. We have technologies to acqu...
Data collecting is necessary to some organizations such as nuclear power plants and earthquake burea...