Difference between revisions of "Data Quality Assurance"
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=== Data Quality Assurance === | === Data Quality Assurance === | ||
| − | Data | + | '''Data Quality Assurance''' is a planned and systematic set of processes aiming to provide the desired confidence that the information embodied in a given data set conforms to established requirements. Data quality considerations are typically grouped as follows: |
| − | * Data Quality Assessment. Data quality assessment is a highly contextual process (dependent on the intended uses of the data) that establishes metrics of data quality along a number of different dimensions ([[Data Quality Standards]]) | + | * [[Data Quality Assessment]]. Data quality assessment is a highly contextual process (dependent on the intended uses of the data) that establishes metrics of data quality along a number of different dimensions ([[Data Quality Standards]]) |
* [[Data Integrity Validation | Data Validation]] that is primarily focused on validating the integrity of data | * [[Data Integrity Validation | Data Validation]] that is primarily focused on validating the integrity of data | ||
* [[Data Cleansing]], the process of correcting and possibly transforming data in order to produce a set that is suitable for use | * [[Data Cleansing]], the process of correcting and possibly transforming data in order to produce a set that is suitable for use | ||
[[Category:Data Quality]] | [[Category:Data Quality]] | ||
Latest revision as of 00:45, 26 October 2021
Data Quality Assurance
Data Quality Assurance is a planned and systematic set of processes aiming to provide the desired confidence that the information embodied in a given data set conforms to established requirements. Data quality considerations are typically grouped as follows:
- Data Quality Assessment. Data quality assessment is a highly contextual process (dependent on the intended uses of the data) that establishes metrics of data quality along a number of different dimensions (Data Quality Standards)
- Data Validation that is primarily focused on validating the integrity of data
- Data Cleansing, the process of correcting and possibly transforming data in order to produce a set that is suitable for use
