A cohesive metadata plane that connects catalog, lineage, data prep, data quality, semantic layer, observability, security, and privacy unleashes the full potential of your data governance strategy. This track covers insights, ideas, and best practices of modern approach to metadata management.
Modern organizations run on data – but if that data is untrustworthy or unavailable at critical moments, decisions and operations suffer. In fact, Gartner estimates that poor data quality costs companies an average of $12.9 million annually. To mitigate such…
The need for high quality, trustworthy data in our world will never go away. Treating data quality as a technical problem and not a business problem may have been the biggest limiting factor in making progress. Finding technical defects, such…
Discover how investing in data quality drives measurable ROI and transforms business performance. Learn key metrics like Data Issue Detection Time (DIDT) and Data Issue Resolution Time (DIRT) to quantify the cost of poor data quality and demonstrate the value of improved data quality.