Data quality characteristics
During the evaluation of data quality itself, the following result have been found. First design quality and quality of conformance are to be distinguished. Design quality is concreted in the information of standards, data definitions and documentation. Quality of conformance focuses on the data contents and the data values. A further important aspect of data quality is quality of the data delivery processes. There, particularly the software components of the overall system have to be considered. The importance of the individual aspects are summarised in Figure 4.
ects are summarised in Figure 4.
If the characteristics of data quality get analysed, consistency is very important. The database should be consistent with regard to the contents and within time. For data values completeness and correctness as well as the representation of missing values are important. Apart from these, availability, timeliness, referential integrity and syntactic correctness of the data value is important. The tracking of the data source and the documentation of insufficient data quality is relevant. Further semantic and identifiably of data are important for data quality. Here a homogeneous, clear and precise description of the data models and data flows is to be named in particular. The precision of value ranges and the granularity of the data models seem to be less critical. System technical aspects, data protection and access rights are less important and are not considered as characteristics of data quality. Data quality characteristics mentioned
by means of an open question are shown in Table 2.
Data quality characteristicsDuring the evaluation of data quality itself, the following result have been found. First design quality and quality of conformance are to be distinguished. Design quality is concreted in the information of standards, data definitions and documentation. Quality of conformance focuses on the data contents and the data values. A further important aspect of data quality is quality of the data delivery processes. There, particularly the software components of the overall system have to be considered. The importance of the individual aspects are summarised in Figure 4. ects are summarised in Figure 4.If the characteristics of data quality get analysed, consistency is very important. The database should be consistent with regard to the contents and within time. For data values completeness and correctness as well as the representation of missing values are important. Apart from these, availability, timeliness, referential integrity and syntactic correctness of the data value is important. The tracking of the data source and the documentation of insufficient data quality is relevant. Further semantic and identifiably of data are important for data quality. Here a homogeneous, clear and precise description of the data models and data flows is to be named in particular. The precision of value ranges and the granularity of the data models seem to be less critical. System technical aspects, data protection and access rights are less important and are not considered as characteristics of data quality. Data quality characteristics mentionedby means of an open question are shown in Table 2.
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