Experian Adds Native Data Quality Tools to Snowflake
Experian has released in-platform data quality tools for Snowflake, allowing users to assess, score, and remediate data directly within the cloud data warehouse. The solution offers data profiling, validation, and enrichment inside the Snowflake ecosystem. This is aimed at helping enterprises in regulated industries like insurance ensure data reliability for pricing and risk modeling.
- This integration embeds Experian's Aperture Data Studio directly into Snowflake's AI Data Cloud, allowing data quality workflows to be executed natively without moving data out of the secure environment. - For insurers, this addresses a critical need for reliable data in pricing and risk modeling; inaccurate property data, for example, can significantly alter modeled losses from natural catastrophes. - The move places Experian in direct competition with other data quality and observability tools within the Snowflake ecosystem, such as Informatica, Collibra, Ataccama, Monte Carlo, and Great Expectations. - This partnership builds on a previous collaboration that integrated Experian's identity graph into Snowflake Data Clean Rooms, primarily for advertising and marketing data sharing. - Key capabilities of the underlying Experian platform include data profiling, standardization, address and email validation, and data enrichment using Experian's proprietary consumer and business datasets. - The integration is a response to stricter data governance requirements in regulated industries, including the Solvency II directive for insurance, which mandates accuracy, completeness, and appropriateness of data for capital calculations. - By processing data in-platform, the solution is designed to reduce the time data scientists spend on data preparation, which can account for up to 80% of their time in developing AI and machine learning pipelines.
