Data Quality
Not all data is created equal. Telmai ensures that every decision is based on reliable data
Request a demoOut-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
Interactively build and manage DQ rules and SLAs
- Interactive guided experience to build and test data quality checks and expectations
- Build complex multi-attribute rules within a table or across multiple tables in the system
- Ability to segment the DQ checks based on customer-defined dimensions like country
360 Degree view into Data Assets
- Enhance data catalog insights with data health insights like open alerts and DQ KPI
- Out-of-the-box integration with data catalog tools like Databricks Unity Catalog and Alation
- REST API support to integrate into any Catalog system
Review and remediation workflows
- Orchestrate stewardship workflows and share suspicious data for approval reviews
- Design remediation workflows based on data quality binning
- Share, export and collaborate on suspicious/bad data
More features
Connect your datasource, or send data via REST, or load a local file
Quickly identify and pinpoint data anomalies, errors, or inconsistencies
Telmai will learn your data and its trends and automatically alert on unexpected drifts
Telmai will finally advice you on next best actions for your data sets
See what’s possible with Telmai
Request a demo to see the full power of Telmai’s data observability tool for yourself