Telmai continuously monitors, detects, troubleshoots, and helps remediates data anomalies and quality issues in structured and semi-structured data for both batch and streaming workloads. Use Telmai with your Delta Lake, Databricks Lakehouse Platform, and Delta Live Tables (DLT) to discover and prevent issues before any downstream impact.
Telmai enables publishing its real-time data health metrics and data quality KPIs, including unresolved issues, into the Unity catalog, so data teams can focus on leveraging trusted data sets for consumption. Our investigator user interface allows faster root cause analysis and resolution by leveraging multiple aspects of data, like its lineage.
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 a well-designed and high-quality data lake environment. With Telmai, migration projects are less risky and completed in a fraction of the time and resources.
Telmai’s powerful, Databricks Spark-based architecture processes and monitors the data (without sampling) across every attribute and every record to give users the highest accuracy and fastest resolutions. Telmai does not push data validation rules into the underlying delta lakes to prevent slowing them down or increasing their costs.
We have shared customers and have gone through technical evaluation with Databricks to ensure our integration is designed for the best performance, architecture, and scale.
For more information, read this blog about our integration.