// Taking on the Data Quality Challenge in the Age of AI

Confidence in the integrity, accuracy, and trustworthiness of data is currently at a low point – at a time when it's more crucial than ever. In this new study, only 23% of DBTA subscribers expressed full confidence in their data, and close to one-third said that data quality is a constant, ongoing issue. What's more, new data analytics and AI projects are how most organizations are finding out about data quality issues.

On the one hand, this is not surprising given the high levels of interest in obtaining business value from the adoption of new analytics and AI technologies. On the other hand, since AI runs on data, it's also a worrying sign. Without good data, all of these exciting projects are not going to succeed, and when it comes to data quality, many organizations struggle with managing project complexities, finding internal support, and accurately determining ROI. Download this study today for the full scoop!