INFS 247 Lecture Notes - Lecture 4: Data Quality, Parsing
19 Jun 2018
School
Department
Course
Professor
INFS Lecture 4
Data Quality
Data quality
oData in an information system is considered of high quality if it correctly and non-
ambiguously reflects the real-world it is designed to represent
oQuality of data used to make business decisions
Accuracy
Uniqueness
Completeness
Consistency
Timeliness
Conformity
Accuracy
oThe extent to which data correctly reflects the real-world instances it is supposed to
depict
Uniqueness
oRequires each real-world instance to be represented only once in the data collection
Completeness
oThe degree to which all the required data is present in the data collection
Consistency
oThe extent to which the data properly conforms to and matches up with the other data
Timeliness
oThe degree to which the data is aligned with the proper time window in its
representation of the real world
Conformity
oThe extent to which the data conforms to its specified format
Preventative data quality actions
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Data quality: data in an information system is considered of high quality if it correctly and non- ambiguously reflects the real-world it is designed to represent, quality of data used to make business decisions. Accuracy: the extent to which data correctly reflects the real-world instances it is supposed to depict. Uniqueness: requires each real-world instance to be represented only once in the data collection. Completeness: the degree to which all the required data is present in the data collection. Consistency: the extent to which the data properly conforms to and matches up with the other data. Timeliness: the degree to which the data is aligned with the proper time window in its representation of the real world. Conformity: the extent to which the data conforms to its specified format. Preventative data quality actions: actions taken to preclude data quality problems. Corrective data quality actions: actions taken to correct the data quality problems.
