Seamlessly plugs into your data ecosystem – any system, any source, any format
Telmai’s open architecture integrates with data lakes and data lakehouses –natively supporting raw formats like Apache Iceberg, Hudi, and Delta Lake
Connect every data source and workflow
- Telmai’s open architecture supports monitoring data across your streams, lakes, and warehouses
- Supports structured and semi-structured data
- No pre-processing or transformation required
- Easily scale your data observability as your data ecosystem changes
Natively connects to open ecosystem
- Directly read formats like Parquet, Avro, JSON, CSV, and XML
- Fully support DQ and monitoring for Apache Hudi,Iceberg and Delta
- Bi-directional integration with open data catalogs like Unity, Datahub, and Polaris (future)
Data Health Dashboard
To monitor the health of your entire data pipeline on an ongoing basis, Telmai provides you with a health dashboard about all your data sources and their respective health metrics. You can see your alerts and data quality KPIs and compare the current state with the last day, week, month, or quarter averages
Highly efficient data pipeline performance
- Robust monitoring capabilities without impacting underlying system performance or inflating infrastructure costs
- Elastic spark architecture enables scalable data profiling, investigation, and detection of data quality issues across your entire dataset
- A dedicated compute layer separate from your data warehouse or analytical databases prevents the overload of your systems
Integrations for seamless orchestration
- REST API- first design for easy integrations with any orchestration or validation tool
- Set up actions based on the status of data pipelines, enabling timely error detection and response
Open Architecture
No-code connection to Data lake and lakehouse –natively support raw formats like Iceberg, Hudi and Delta
Data Quality
Validate every value before ingesting into AI-model, automate and orchestrate DQ workflows in AI-workloads
Anomaly Detection
No sampling, ML-driven anomaly detection on column-values and business metrics
Data Layer Consistency
Improve quality across bronze, silver and gold layers embedded design patterns to stop bad data at bronze
Data Health Analysis
No code analysis and reporting of your data lake and lake house
Incident Management
Alerting, ticketing, investigation and remediation workflows