Reduce cloud costs and improve data quality in your data lakehouse

Automate and orchestrate data observability into each layer of medallion architecture with Telmai.

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Identify and resolve data issues at thier source

Low-code integration directly into source systems
Automatic upstream monitoring for schema, volume, duplicates, and freshness
Process any raw data with any schema, including semi-structured

Detect issues during data transfer into the bronze layer

Automatic DQ checks: freshness, schema drift, volume
Automatic cross-system consistency checks across raw and bronze data
Define and manage validation rules (optional)

Ensure data is accurate and reduce the cost of transfer and query for bad data

Circuit breaker pattern to stop bad data ingestion into the silver layer
DQ binning to separate and store suspicious data in low-cost storage
Define and manage validation rules.

Data is consumption-ready and meets the DQ SLA of individual business teams

Automatic anomaly detection on business metrics
Set business team-driven DQ policies and notification
Downstream lineage

Telmai’s ability to provide insights into data observability and quickly identify where data quality improvements can be made allows our team to focus on the business impact and help streamline our analysis. Folks across all technical abilities are able to use Telmai to help answer business questions and easily get insights that help us improve quality.

Head of data governance

Fortune 200 global real estate firm