Is poor data quality letting your AI down?

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The most successful businesses in the future will be those that optimize their AI investment. As companies start their journey to AI readiness, they must develop robust data management strategies to handle increased data volume and complexity, and ensure trusted data is available for business use. Poor quality data is a burden for users trying to build reliable models to extrapolate insights for revenue-generating activities and better business outcomes.

It’s not unusual for business users to prioritize access to the data they need over its quality or usability. The simple truth is if an organization has bad quality data and uses it to feed AI tools, it will inevitably deliver poor quality and untrustworthy results.

Jay Limburn

Chief Product Officer, Ataccama.

Why data quality matters

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