Data Quality
Continuously monitor data quality rules, issues, and dataset readiness across customer experience data assets.
Monitored Datasets
5
Continuous rule monitoring
Healthy Datasets
2
All configured rules passing
Active Quality Issues
6
Not yet resolved
Critical Quality Issues
2
Requires immediate review
Quality flow
- Incoming Data
- Quality Rules
- Validation
- Pass?
- Available for Processing / Quality Issue
- Assigned Owner
- Correction
- Revalidation
- Resolved
Quality status is surfaced from NWC's existing Data Quality environment. This platform provides visibility and analytical impact, not a replacement quality tool.
Quality dimensions
Standard dimensions used for monitoring in this prototype.
Completeness
Required fields are populated in the incoming data.
Validity
Values conform to the expected format and allowed range.
Consistency
Values agree across related datasets and source systems.
Uniqueness
Records are not duplicated within the dataset.
Timeliness
Data arrives within the expected processing window.
Quality scores are a prototype analytical representation and do not reflect an official NWC scoring formula. Showing 6 issues and 13 rules.
Quality overview
Dataset-level quality standing.
Active Data Quality Issues
Select an issue to review its rule, history and downstream impact.
Data Quality Rules
Continuously evaluated rules per dataset.
Data Quality Over Time
Prototype trend across the last twelve weeks.
Source names, dataset names, record counts, quality scores, metadata values and lineage relationships shown here are simulated prototype data used for design validation. Data quality scoring, thresholds and completeness percentages are prototype representations and do not reflect an official NWC formula. Relevant assets are expected to synchronise with the NWC central data catalog and existing Data Quality environment rather than be replaced by this platform.