Data quality rules, pipeline validation and issue resolution
Manage data quality rules in a central repository, run continuous validation within pipelines, and assign issues to stewards with alerts to support resolution.
How does Loome Data Ops support data quality?
Loome Data Ops centralises data quality rules, runs continuous checks within pipelines, and supports issue assignment and resolution through stewardship workflows and targeted alerts.
Data Pipeline and Rule Discovery
Find data pipelines and quality rules across multiple platforms through a single interface.
Centralised Rules
Manage and execute data quality rules across your data estate from a central repository.
Automated Validation
Run continuous data quality validation checks within your pipelines.
Stewardship Workflow
Assign data quality issues and track them through to resolution.
Alert Management
Configure and send targeted data quality alerts to operational staff.
Time Series Analytics
Store and analyse quality and performance metrics of your data warehouse or lakehouse.
Data quality operations with Loome Data Ops
Accelerate Issue Resolution
- Automated detection and alerts
- Streamlined stewardship workflow
- Real-time operational feedback
Strengthen Data Trust
- Centralised quality rule management
- Automated reconciliation checks
- Complete audit trail of resolutions
Drive Accountability
- Role-based ownership
- Integrated feedback collection
- Comprehensive issue tracking
Start your free trial and see how Loome can transform your data quality operations
Data quality workflows, reference data and data integrity
Data Mapping
Capture ETL design and data model decisions, then publish them in context within your reports.
Manage reference data online
We provide a simple way to manage manual reference data for your analytics solution so you can stop worrying about having to build integration processes for all of your disparate spreadsheets. A cloud native alternative to SQL Server Master Data Services at a fraction of the cost.
Monitor and resolve data quality issues
The workbench lets analysts and data stewards participate in data quality workflows. Assign responsibility for an issue and track actions through to resolution.
