Case Study: DataStax achieves trusted product usage data at scale with Telmai

DataStax Builds Trust in Product Usage Data with Telmai

DataStax, a real-time data company, faced a challenge ensuring the quality of product usage data collected from its database logs for 36,000 clusters. Their in-house data quality solution was unable to reliably distinguish between true drops in customer usage and false positives caused by pipeline failures, leading to untrustworthy reports. This required significant manual overhead for investigation, prompting their search for an automated solution from a vendor like Telmai.

The solution was the implementation of Telmai's ML-based data observability platform. Telmai automates the monitoring of actual data values for accuracy, completeness, and uniqueness, tracking drifts and anomalies in usage metrics like read/write operations and new cluster creation. As a result, DataStax achieved higher trust in its data for business teams and leadership, gained the ability to detect unknown issues proactively, and can now observe data at scale across its massive cluster environment without increasing headcount.

DataStax

Raghu Nadiger

Data & Analytics Leader