Difference between revisions of "Data Quality"
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(Created page with "Data Quality refers to the quality of the data that is measured by several factors such as accuracy, completeness and many other more. Data quality can be used to detect any errors so that the problems could be resolved. Data quality is related to data consistency and data governance as both of it aim to make the data consistent through the system. ==Data Quality Dimensions== There are several factors that determine the data quality, such as: * Availability * Accuracy...") |
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[[{{PAGENAME}}]] refers to the quality of the data that is measured by several factors such as accuracy, completeness, and many other more. {{PAGENAME}} can be used to detect any errors so that the problems could be resolved. | |||
{{PAGENAME}} is related to data consistency and data governance as both of its aim to make the data consistent through the system. | |||
{{#widget:YouTube|id=5HcDJ8e9NwY&ab}} | |||
==Data Quality Dimensions== | ==Data Quality Dimensions== | ||
There are several factors that determine the data quality, such as: | There are several factors that determine the data quality, such as: | ||
* Availability | *Availability | ||
* Accuracy | *Accuracy | ||
* Comparability | * Comparability | ||
* Completeness | *Completeness | ||
* Consistency | * Consistency | ||
* Flexibility | *Flexibility | ||
* Plausibility | *Plausibility | ||
* Relevance | *Relevance | ||
* Timeliness | *Timeliness | ||
* Uniqueness | * Uniqueness | ||
* Validity | *Validity | ||
==Importance of Data Quality== | ==Importance of Data Quality== | ||
As more company are becoming more data-driven, data quality is important as low-quality data might resulting the company to have the wrong decision. Current technologies that are using artificial intelligence and automation also depends on good data quality to have | As more company are becoming more data-driven, data quality is important as low-quality data might resulting the company to have the wrong decision. Current technologies that are using artificial intelligence and automation also depends on good data quality to have more accurate data and better result. | ||
Revision as of 03:21, 26 August 2022
Data Quality refers to the quality of the data that is measured by several factors such as accuracy, completeness, and many other more. Data Quality can be used to detect any errors so that the problems could be resolved.
Data Quality is related to data consistency and data governance as both of its aim to make the data consistent through the system.
Data Quality Dimensions
There are several factors that determine the data quality, such as:
- Availability
- Accuracy
- Comparability
- Completeness
- Consistency
- Flexibility
- Plausibility
- Relevance
- Timeliness
- Uniqueness
- Validity
Importance of Data Quality
As more company are becoming more data-driven, data quality is important as low-quality data might resulting the company to have the wrong decision. Current technologies that are using artificial intelligence and automation also depends on good data quality to have more accurate data and better result.