Experian brings in-platform data quality tools to Snowflake

Experian has launched an integration between its Aperture Data Studio product and Snowflake's AI Data Cloud, allowing organisations to run data profiling, transformation and validation inside Snowflake.

The companies described the move as a response to growing demand for stronger data controls as businesses expand their use of AI and advanced analytics. The integration is available globally, including in Australia and New Zealand.

Aperture Data Studio includes data quality logic that can be applied directly to datasets stored in Snowflake, keeping data in-platform rather than exporting it for external processing.

In-platform processing

The integration executes data quality workflows "where the data lives", an approach that can appeal to organisations handling regulated or sensitive information. Many have tightened internal policies on data movement in response to privacy rules, customer expectations and increased scrutiny of how data is used in AI development.

Users create workflows in Aperture Data Studio's interface and run them in Snowflake, enabling joint customers to validate data and fix issues without moving datasets outside the Snowflake environment.

The integration is also positioned to support governance and compliance. Customers can use the tools for cataloguing and control activities alongside data quality processes, aiming to reduce errors and improve trust in downstream analytics and AI outputs.

Data quality focus

Data quality has become a key issue in AI programmes, particularly when organisations train models on internal datasets or use AI systems for decisions with compliance implications. In many sectors, firms must show how data was sourced, prepared and governed, including financial services, healthcare and insurance.

Vendors have increasingly bundled data observability, governance and quality tools around cloud data platforms as enterprises consolidate data estates. The Experian-Snowflake tie-up fits that trend, focusing on delivering controls within a widely used data cloud rather than through separate infrastructure.

Daniel Drake, Managing Director, Data Quality, Experian A/NZ, said the company sees a widening gap between ambition and execution as AI use rises across the region.

"Data is the foundation of every digital and AI-driven transformation, yet many businesses across Australia and New Zealand struggle to turn it into real business value. As AI and advanced analytics accelerate, the stakes have never been higher," Drake said.

He said the integration combines Experian's data quality and governance capabilities with Snowflake's platform.

Drake said, "Our collaboration with Snowflake brings together Experian's expertise in data quality and governance with the scale, performance and flexibility of Snowflake's platform. This will enable businesses in our region to not only innovate faster, stay compliant, and reduce risk but also make trusted data a reality. This is just the start of our joint efforts to bring Experian's powerful data quality capabilities to where Snowflake customer data lives."

Partner ecosystem

The launch also highlights Snowflake's growing partner ecosystem around its AI Data Cloud. Snowflake has encouraged software vendors and services partners to build products that operate within its environment, a strategy aimed at reducing friction for customers that prefer fewer data copies and fewer processing locations.

Rinesh Patel, Global Head of Financial Services, Snowflake, said the integration is intended to give joint customers a stronger foundation for compliance and risk management as they expand AI use cases.

"With the launch of Experian's integration with the Snowflake AI Data Cloud, we look forward to driving deeper value for our joint customers. This integration enables customers to build a trusted, compliant data foundation that reduces risk, accelerates AI adoption and supports smarter decision‐making," Patel said.

Experian described Aperture Data Studio as a platform that combines data quality and governance for data, models and AI agents in a single product. With the Snowflake integration, those workflows are now available to customers managing data on Snowflake.

Both companies said they plan to continue work under the partnership, including further efforts to bring data quality processes into the environments where customers store and manage datasets.