Several dimensions define data quality in a business context:
Accuracy: Data should be free from errors and reflect the real-world entities or events it represents. Completeness: All necessary data should be present. Missing data can lead to incorrect analyses. Consistency: Data should be consistent across different databases and systems. Timeliness: Data should be up-to-date and available when needed. Relevance: Data should be pertinent to the business context and support the decision-making process. Reliability: Data should be trustworthy and sourced from reliable origins.