Description
At ZoomInfo, data quality forms the foundation of its product offerings, driving the business’s ability to provide accurate, timely insights to its global clients. Any lapses in data quality that could directly impact customer experience and trust are risks they cannot afford.
At ZoomInfo, data quality checks are embedded within their data processing and orchestration flows.
Learn how to leverage the principle of data quality binning, which is a preprocessing technique for segregating ‘suspicious’ data from your pipeline and allowing ‘good’ data to flow downstream of it. This segregation ensures that only accurate and reliable data flows through ZI data pipelines, while erroneous data is set aside for further analysis or correction.
Join Pankaj Yawale, Senior Principal Data Architect at ZoomInfo, and Mona Rakibe, Co-founder and CEO of Telmai, to understand how ZoomInfo built a scalable data architecture across multi-cloud platforms to process complex semi-structured data. Learn how ZoomInfo ensured a continuous flow of reliable data insights while leveraging Telmai's AI-powered data quality and automated remediation workflows for end-to-end data reliability.
This session will cover architectural decisions, implementation challenges, and key learnings valuable for teams building large-scale data platforms.