Case Study: RingCentral achieves real-time quality-of-service analytics with IBM StreamSets

RingCentral Dials Up a Data Lake for Quality of Service, Fraud Detection and Product Usage Analytics

RingCentral, a global cloud unified communications provider serving over 350,000 business customers and processing more than 200 million calls per month, faced challenges ingesting and harmonizing high‑volume, complex call detail records (CDRs) to support a 360° view of conference calls and other analytics. To address real‑time pipeline and ETL complexity, RingCentral partnered with IBM StreamSets and adopted the IBM StreamSets DataOps Platform to feed an AWS S3 data lake.

IBM StreamSets built and now manages RingCentral’s data pipelines into an AWS S3 data lake, enabling unified dataflows, optimized data‑movement topologies, and broad ETL across diverse sources so multiple analytics solutions can run from the same dataset. As a result, RingCentral gained immediate, reliable access to real‑time data at scale—supporting analytics across their 200M+ monthly calls and 350K customers—and is expanding democratized data science and predictive use cases such as churn prediction, network issue detection, fraud identification, and marketing spend analysis.

RingCentral

Michael Becker

Senior Director of Big Data