Reasons to Be Excited About Snowflake Partnership | Collibra

What you'll learn

• Use predictive data quality and observability, along with the power of machine learning, to generate adaptive data quality rules and identify data errors early on in the lifecycle before bad data makes its way into the hands of users. - Maintain compliance at scale by continuously monitoring data for completeness, timeliness, accuracy, and validity. - Reduce the risk and cost of migrating data by validating the integrity of data between its source and the Snowflake ecosystem. - Build trust by proactively detecting and remediating data issues , and by translating enterprise data governance standards into data quality rules that ensure complete, consistent, and accurate data.

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