Out of the Box Data Quality Scoring for Snowflake

Many companies have benefited from the Snowflake cloud-native data platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization. The leading-edge Snowflake architecture delivers a single and seamless experience across multiple public clouds which allows organizations of all sizes to unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads.

Why should users then handcuff their advanced data clouds with out-of-date inferior data quality and data catalog solutions? These traditional solutions are burdensome requiring a great deal of manual interaction. They typically have not scaled with the growth in datasets being ingested, resulting in only a small percentage of the data being properly assessed for quality.

In this webinar, let’s jump into the next generation of data management by using an augmented data platform with automated data discovery and data quality – all out of the box.

As part of this session, Raj Joseph, CEO of DQLabs shall present a demo of DQLabs.ai and demonstrate how you can make all of your data assets on Snowflake and other sources instantly discovered and searchable with ready-made Data Quality measurement and monitoring –automated to reduce your Time to Value.

Webinar Highlights

• A thorough overview of the Modern Data Stack and where Snowflake with DQLabs fits in.
• Learn how you can leverage augmented technologies to manage your modern data stack.
• A demonstration of the DQLabs.ai AI/ML augmented data platform with specific use cases around off the shelf data discovery and data quality.