Within data quality, you'll find five traits: accuracy, completeness, reliability, relevance, and timeliness.
Data quality is essential - it evaluates whether data can fill its need in a specific setting (like information examination, for instance). All in all, how would you decide the nature of a given arrangement of data? There are Data quality attributes of which you ought to know.
There are five attributes that you'll find inside Data quality: precision, fulfillment, dependability, significance, and practicality - read on to find out more.
Accuracy
Completeness
Reliability
Relevance
Timeliness
| Characteristic |
How it’s measured |
| Accuracy |
information correct in every detail? |
| Completeness |
How guide is the information? |
| Reliability |
Does the information contradict other trusted resources? |
| Relevance |
Do you really need this information? |
| Timeliness |
How up- to-date is information? Can it be used for real-time reporting? |
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Answered one year ago
Matti Karttunen
Data quality is essential - it evaluates whether data can fill its need in a specific setting (like information examination, for instance). All in all, how would you decide the nature of a given arrangement of data? There are Data quality attributes of which you ought to know.
There are five attributes that you'll find inside Data quality: precision, fulfillment, dependability, significance, and practicality - read on to find out more.
Accuracy
Completeness
Reliability
Relevance
Timeliness
You May Also Like: Why is Python better than JavaScript for data science?