What is Data Quality - Definition, Dimensions & Characteristics
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What is Data Quality - 
Definition, Dimensions & 
Characteristics 1
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Data quality measures the condition of data, relying on 
factors such as how useful it is to the specific purpose, 
completeness, accuracy, timeliness (e.g., is it up to date?), 
consistency, validity, and uniqueness. 
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DATA QUALITY 
DIMENSIONS
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The data must conform to actual, real-world scenarios and 
reflect real-world objects and events. Analysts should use 
verifiable sources to confirm the measure of accuracy, 
determined by how close the values jibe with the verified 
correct information sources.
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Completeness measures the data's ability to deliver all the 
mandatory values that are available successfully.
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Data consistency describes the data’s uniformity as it 
moves across applications and networks and when it 
comes from multiple sources. Consistency also means that 
the same datasets stored in different locations should be 
the same and not conflict. Note that consistent data can 
still be wrong.
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Timely data is information that is readily available 
whenever it’s needed. This dimension also covers keeping 
the data current; data should undergo real-time updates to 
ensure that it is always available and accessible.
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Uniqueness means that no duplications or redundant 
information are overlapping across all the datasets. No 
record in the dataset exists multiple times. Analysts use 
data cleansing and deduplication to help address a low 
uniqueness score.
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Data must be collected according to the organization’s 
defined business rules and parameters. The information 
should also conform to the correct, accepted formats, and 
all dataset values should fall within the proper range. 
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• Make sure that top-level management is involved. Data 
analysts can resolve many data quality issues through 
cross-departmental participation.
• Include data quality activity management as part of 
your data governance framework. The framework sets 
data policies and data standards, the required roles 
and offers a business glossary.
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THANK YOU
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