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Discover how Telmai enhances BigQuery data reliability through automated anomaly and drift detection.
Learn how Telmai is aiding companies in trusting their data and ensuring that their AI models produce effective results.
Build Trusted Analytics and Data Products Faster
Telmai’s low-code, no-code data observability product proactively detects data quality issues, anomalies and drifts in BigQuery, GCS, DataFlow, Pub/Sub events, and other sources to help data teams create and monitor their data products, analytics and reporting, streaming applications, and advanced machine learning models faster and at a fraction of the cost and resources.
Data Accuracy at the Record Value Level
Telmai uses both ML and user-defined expectations to observe data values as well as metadata in BigQuery, providing higher accuracy and understanding of data that feeds analytics applications, advanced machine learning models, and data products.
Performance and Scale at Low TCO
Telmai’s petabyte-scale platform, built on Spark and Google Cloud Services (GCP) including Google Dataproc, decouples its data quality analysis and scoring from the underlying data warehouses and analytical databases, and provides customers with data quality monitoring capabilities without overloading and slowing down these operational systems or increasing their infrastructure costs.
Fasttrack Cloud Migrations
With Telmai, migration projects to Google Cloud and Google BigQuery are done within a fraction of the time. Telmai’s low-code no-code approach enables profiling and understanding of data quality issues prior to migration, and testing and validation after migration to ensure duplicates, inconsistencies, and errors did not sneak into the new system.
Become a partner
Request a demo to see the full power of Telmai’s data observability tool for yourself.