🎯 Data Governance
Data Quality & Reliability
Complete audit, anomaly detection and governance for data you can truly rely on. Informed decisions start with reliable data.
Quality Scores
97%
Completeness
94%
Accuracy
98%
Consistency
91%
Freshness
Overall score: 95/100 — Excellent
Dimensions
The 6 dimensions of quality
We evaluate your data across 6 measurable axes, each with validation rules and alert thresholds.
Completeness
No mandatory field should be empty. We identify systemic gaps and their origins.
Accuracy
Do values match reality? Validation by external references and business rules.
Consistency
No contradictions between systems. Same client, same value in CRM, ERP and warehouse.
Uniqueness
Duplicate elimination — at row, entity and cross-system level.
Freshness
Is the data up-to-date? Monitoring of ingestion latency and SLAs.
Conformity
Compliance with formats, value ranges and regulatory constraints (Law 25, GDPR).
Process
Our audit process
1
Profiling
Statistical analysis of each column: nulls, distributions, outliers
2
Validation Rules
Definition of business rules and alert thresholds with your teams
3
Continuous Monitoring
Quality dashboards updated at each data ingestion
4
Remediation
Anomaly correction, cleaning pipelines and regression prevention
Dashboard
Data Quality Dashboard
Dataset quality — Global view
847
Datasets audited
2.3K
Anomalies detected
14K
Validation rules
95%
Average score
Tools
Technologies & tools
Great Expectations
dbt Tests
Soda Core
Apache Griffin
Monte Carlo
dbt
Airflow
Atlan
Alation
Python
SQL
Grafana
Results
Measurable results
97%
average completeness achieved
3×
fewer production errors
40%
time saved on data cleaning
0
major data incident