Scale & Performance
1,000+ tables monitored, 50+ pre-configured checks, under 5-minute issue detection, and 80% remediation automation target.
Solution Accelerator
Data Quality & Observability Accelerator
Automated data quality monitoring in 2-3 weeks.
Architecture & Workflows
Quality and observability architecture for proactive data monitoring across governed lakehouse assets.
Monitor 1,000+ Unity Catalog tables with automated quality checks, ML-powered anomaly detection, intelligent alerting, remediation workflows, PII detection, and governance integration.
Built for production scale and reliability.
1,000+ tables monitoredML anomaly detection80% automated remediationPII detection37+ documents
Quality Dimensions
Null checks, required fields, duplicate detection, key validation, format checks, range checks, and referential integrity.
ML & Anomaly Detection
Three pre-trained ML models, statistical detection, Isolation Forest, LSTM patterns, and false-positive targets under 5%.
Observability
Six dashboards, 0.0-1.0 quality score, Slack/email/PagerDuty alerts, and OpenAPI 3.0 compliant REST integration.
What the accelerator brings into the engagement.
Enterprise Scale
Monitor 1,000+ tables with scheduled checks, parallel execution, metadata-driven configuration, and governed onboarding.
Quality Dimensions
Completeness, uniqueness, validity, consistency, and timeliness checks with flexible thresholds and business rules.
ML Anomaly Detection
Statistical models, Isolation Forest, and LSTM time-series detection help identify issues in under 5 minutes.
Intelligent Alerting
Slack, email, and PagerDuty routing with severity handling, deduplication, aggregation, and SLA views.
Automated Remediation
Workflow orchestration and remediation strategies automate common quality issue resolution patterns.
Dashboards
Quality overview, anomaly detection, remediation tracking, SLA compliance, trends, and PII detection dashboards.
PII Detection
Automated classification and masking patterns for GDPR and HIPAA-oriented data protection needs.
Unity Catalog Integration
Native Unity Catalog support with lineage tracking and metadata-driven quality control.
Implementation assets, documentation, and support.
Implementation
Quality framework, Unity Catalog integration, rules, dashboards, and ML models.
Documentation
Architecture, operations, remediation, onboarding, and quality metric guides.
Automation
Automated checks, alerts, remediation workflows, PII detection, and quality scoring.
Support
Deployment support, onboarding, tuning, training, and post-deployment assistance.
Structured path to production.
Week 1
Framework deployment, Unity Catalog integration, initial onboarding, and ML model deployment.
Week 2
Rule configuration, anomaly tuning, dashboards, and alerting.
Week 3
Full table onboarding, remediation workflows, PII detection, and handoff.
Where this accelerator fits.
Proactive Monitoring
Detect issues before they impact business decisions.
ML Model Quality
Protect training data quality and prevent model degradation.
Compliance & Audit
Show quality metrics, PII detection, and audit trails.
Cost Reduction
Reduce engineering overhead on recurring data quality issues.
Faster than custom delivery.
$200k+ custom build
Custom observability can take 24-36 weeks.
$60k accelerator
Accelerator delivery targets 2-3 weeks.
80% automation
Automated remediation reduces recurring manual effort.
Get Started
Ready to take your business to the next level?
See how Data Quality Observability can transform your infrastructure.