ZoomInfo Uses Telmai to Automate Data Quality at Scale, Over Billions of Data Records and Across Multiple Cloud Sources

A leading go-to-market platform provider, ZoomInfo leverages Telmai to achieve scalable, proactive data quality monitoring across its data ecosystem, boosting accuracy and efficiency.

Telmai, the AI-powered, open-architecture data observability company, proudly announces ZoomInfo as its newest client. Through this partnership, ZoomInfo now leverages Telmai’s machine learning-driven data quality monitoring platform to proactively manage and enhance data integrity across its extensive data ecosystem, with near-term plans to integrate connections to open table formats such as Apache Iceberg.

As the go-to-market platform to find, acquire, and grow customers, ZoomInfo processes over 1.5 billion data points daily to deliver critical insights to more than 35,000 businesses worldwide. Ensuring accuracy, consistency, and timely delivery are essential for maintaining customer trust and operational success. While ZoomInfo invested substantial resources in maintaining data quality, the company recognized the need for an advanced solution to automate data quality at scale while addressing issues proactively across its multi-cloud infrastructure and handling the scale and complexity of its data without imposing significant resource overhead.

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ZoomInfo’s data is distributed across warehouses like Snowflake and BigQuery, as well as data lakes like S3 and GCS that contain data in flat file formats or open-table formats like Iceberg. The company’s primary goals included enhancing the customer experience through full-volume data quality monitoring, automated anomaly detection, and streamlined remediation workflows, all while ensuring compatibility with existing systems and supporting long-term sustainability.

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Designed for ease of use and scalability, Telmai’s intuitive interface made it easy for various business and data engineering teams at ZoomInfo to adopt without extensive training and with minimal setup time. Connecting and scanning new data sources took just minutes, a sharp improvement over the weeks or months required by other solutions.

“During the pilot, Telmai’s ML-driven anomaly detection flagged record-level issues among billions of data points, enabling our team to take actionable steps and generate tickets to address these concerns within hours, outperforming any other data quality tool we’ve evaluated,” said Dr. Ethan D. Peck, Director of Data Engineering at ZoomInfo. “Operating entirely within ZoomInfo’s GCP setup, Telmai handled the onboarding of complex tables and allowed us to retain complete control over our data, eliminating external data transfers and avoiding the high costs of third-party processing.”