AI relies heavily on data, risking quality loss and creating trust issues. Organizations lose revenue due to low-quality data, impacting AI model performance and business decisions.
Data curation takes up significant time for data scientists, hindering model creation. Fragmented data sources affect AI's view of the enterprise, requiring a unified approach for improved accuracy.
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