Learn Why Data Quality Metrics
Matter for Unstructured Data
Founder & CEO, DQLabs
Snowflake is a multi-cloud data warehouse optimized for analytics workloads and requires minimal maintenance. Customers choose Snowflake to unlock the potential of data and AI, empowering better decision-making and superior customer experiences. Modern organizations are increasingly turning to Snowflake’s platform to consolidate their data, enabling seamless access for purposes ranging from business insights to advanced analytics and machine learning. However, the value of dashboards and data-driven tools relies entirely on the quality of the data they depend on.
The DQLabs and Snowflake partnership enables out-of-the-box data observability and data quality for Snowflake, reducing data downtime and improving data accuracy. Simply connect and monitor data across your modern cloud data warehouse for data quality issues and remediation in minutes. The DQLabs platform not only observes the data within your Snowflake instance, so you can be the first to know about potential data issues, but also facilitates your centralized data quality stewardship and discovery process seamlessly. With DQLabs, customers can quickly start monitoring any Snowflake table in just a few minutes. No complex coding or time-intensive setup required. DQLabs leverages AI-driven data quality monitoring to proactively identify and resolve data quality issues, including their root causes, before they impact BI dashboards, reports, or downstream AI models.