Gartner reports poor data quality costs organizations $10.8 million yearly, likely increasing in digitalized business environments. AI's significance is evident, with Accenture noting a 40% higher share price likelihood when leaders mention AI. Widespread AI use hinges on quality training data, emphasizing the need for a robust data quality strategy.
To capitalize on AI insights, organizations need a deliberate data quality strategy. As a data leader, ensure an organized approach with necessary tools and processes in place with this eBook from our partners at Informatica that explores The Art of Mastering Data Quality for AI and Analytics: 7 Essential Tips for IT Leaders.