digna Modules — Technical Overview¶
Modules for Data Quality, Quality of Data, and Observability of Data – digna Platform
digna is an AI-powered Data Quality & Observability Platform designed for in-database execution.
It operates directly inside your data environment and ensures trust in your data — without requiring manual rule coding or data movement.
By combining automated anomaly detection, rule-based validation, and data structure monitoring, digna continuously improves both data quality and observability of data pipelines.
Module Summary¶
| Module | Focus Area | Key Capabilities |
|---|---|---|
| Data Anomalies | Automated anomaly detection | Learns “normal” data behavior, detects deviations in volume, distribution, or value patterns, and flags abnormal data movement or gaps |
| Data Analytics | Trends & volatility | Analyzes long-term metrics, stability, and change patterns to detect drifts in data quality over time |
| Data Validation | Rule-based checks | Enforces exact values, ranges, thresholds, or reference lists — with full audit trail and reproducibility |
| Data Timeliness | Delivery monitoring | Uses AI-learned expected arrival times and user-defined schedules to detect late or missing data |
| Data Schema Tracker | Structural monitoring | Detects schema drift, such as new or removed columns, renamed fields, or datatype changes |
How the Modules Work Together¶
Each digna module addresses a specific dimension of the quality of data and observability of data systems, yet they integrate seamlessly into a single platform.
- Data Anomalies and Data Analytics provide AI-driven insights and trend awareness.
- Data Validation ensures correctness through rule enforcement.
- Data Timeliness safeguards data delivery and freshness.
- Data Schema Tracker protects structure and metadata integrity.
Together, they create a complete Data Observability and Quality Control Framework operating entirely within your environment — on-premises or private cloud.
Benefits of the Modular Approach¶
- Scalable – start with one module and expand as needed
- Unified Interface – same UI and API for all modules
- AI-Assisted Configuration – minimal setup effort, fast onboarding
- Cross-Module Insights – detect relationships between timeliness, schema drift, and anomalies
- Enterprise Integration – works with Teradata, Snowflake, Databricks, and other enterprise data platforms
digna delivers a modular, AI-driven framework for Data Quality and Data Observability —
built in Europe for organizations that demand data sovereignty, performance, and trust.
All modules work together to provide complete visibility into your data ecosystem, ensuring that every insight is accurate, explainable, and reliable.
Frequently Asked Questions¶
Do I need all modules to start?
No — each module can be licensed and deployed independently.
How does digna detect anomalies?
Through AI models that learn from historical patterns in data volume, distribution, and value ranges.
Can digna validate both technical and business rules?
Yes — the Data Validation module supports both types of checks with audit-ready reports.
Does digna require external services or SaaS?
No. All digna modules operate inside your own infrastructure for full data control and compliance.