Thirsty for Data Quality?
Quench your thirst for data with a personalized demo of Telmai and learn how we can help transform your data-driven organization!
Schedule & Attend a demo and score big with a sought-after Stanley Quencher cup to take home. Schedule time now!
*Must attend meeting and be involved in an active or upcoming analytics initiative to qualify.
Out-of-the-box Data Quality report
- Continues automatic classification and reporting of observability learnings into Data Quality KPIs like completeness, correctness, uniqueness, timeliness, validity, and accuracy
- Human-in-the-loop approach to take users’ inputs into the definition of data quality KPI
- Compare the current state of your data quality KPI with historical data to monitor progress
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
Spot anomalies before they impact your business
Telmai employs machine learning and statistical analysis to automatically generate thresholds for both custom and predefined data health metrics
- Column value level anomaly detection for things like value outliers, out-of-range values, and unexpected value
- Telmai’s thresholds are self-evolving, based on historical data from your systems
- Telmai’s AI engine continually revises and refines thresholds, ensuring precise monitoring and timely insights into your data’s performance and quality
Stop bad data instream
- Stop bad data at the source before it impacts downstream
- Control data pipeline flow based on ML-based anomalies or manual validations SLAs
- Define the next actions when data fails to meet DQ SLA’s
