Data Quality Definition
Data quality meaning refers to the accuracy, completeness, and consistency of data.
Data quality can be evaluated on various data quality dimensions:
- Completeness: Refers to whether all the required data is available
- Accuracy: Measures the degree to which the data reflects the truth
- Consistency: Refers to whether the data is uniform and coherent across all sources
- Timeliness: Refers to whether the data is up-to-date and relevant
- Relevancy: Measures whether the data is applicable to the business problem at hand.
In today's data-driven world, data quality is critical to business operations and decision-making. Poor quality data can lead to incorrect insights, ineffective decision-making, and missed opportunities.
For example:
If you had the same type of data appearing in different formats, with conflicting records, that data would not have a high level of consistency and could be considered low quality.
Learn everything about data quality software on our platform page. Whether you’re a novice or a seasoned expert in the topic, it’s a valuable resource to ensure that your data is upholding the highest quality standards.
