Data Security
AI Infrastructure
The measure of data’s fitness to serve its intended purpose in a given context.
Detailed Explanation
Data Quality refers to the overall condition and reliability of data, assessing how well it meets specific requirements for accuracy, completeness, consistency, and timeliness. High-quality data ensures effective decision-making, reduces errors, and enhances AI model performance by providing trustworthy information. Maintaining data quality is essential for building robust, accurate AI systems and reliable infrastructure.
Use Cases
- •Use case: Improving model accuracy by regularly validating and cleansing datasets to ensure high data quality for all AI training and deployment processes.
Related Terms
Other terms in the AI Infrastructure category