What is Data Relevance? Definition, Examples, and Best Practices

Data relevance is the degree to which data provides insight into a real-world problem or purpose being addressed and contributes to the overall understanding of the business. It is one of the ten dimensions of data quality, which also includes completeness, consistency, accuracy, and timeliness. Irrelevant data can lead to poor decision-making and damage a company's reputation. To measure data relevance, teams can use metrics such as data usage, time to analysis, and feedback from users. Ensuring data relevance involves identifying user needs, monitoring trends over time, and using data observability tools to assess the usefulness of data.