Changelog – Release 2026.04¶

With Release 2026.04, digna significantly enhances its capabilities in analytics and data validation.
This release introduces advanced time-series analysis, reusable validation components, and centralized value standardization.

🚀 New Features¶

Analytics Chart – Time Series Analysis Without Data Science¶

• New Analytics Chart for interactive time-series analysis
• Built-in analytical methods:
  • Linear, quadratic and cubic regression
  • Piecewise regression with configurable breakpoints
  • Smoothing techniques
  • Quantile analysis
• Automatic identification of trends, seasonality, and pattern changes
• Residual analysis for deeper insight into deviations
• Time-series are automatically calculated for every dataset

Impact: Enables users to understand complex data behavior over time without requiring data science expertise or external tools.

Enumerations – Central Definition of Allowed Values¶

• Define reusable sets of allowed values (e.g., countries, states, status codes)
• Validate column values against predefined enumerations in digna Data Validation
• Reuse enumerations across projects and data sources
• Use enumerations everywhere via #ENUM:MY_ENUM#
• All check are executed directly in the source database

Impact: Ensures consistent and standardized data values across the organization.

Validation Rule Templates – Reusable Data Quality Logic¶

• Define reusable validation rules (e.g., whitespace checks, NOT NULL, format checks)
• Apply templates across multiple datasets
• Ensure consistent rule logic across projects
• Reduce duplication and manual configuration
• All check are executed directly in the source database

Impact: Enables scalable and high-performance data validation without data movement.

Column-Level Relevance Conditions¶

• Define relevance conditions on column level for each statistic
• Extends the concept of anomaly relevance conditions
• Control when a statistic should be considered relevant
• Reduce noise by excluding non-critical situations

Impact: Improves signal quality by focusing only on meaningful deviations.

🧪 Extended Data Analytics & Validation Capabilities¶

With this release, digna expands both data understanding and data validation standardization:

• Advanced time-series interpretation without data science knowledge
• Centralized definition of allowed values via enumerations
• Reusable validation logic via templates
• Fine-grained control over relevance of statistics and alerts

Together, these capabilities enable organizations to not only detect issues, but also understand, standardize, and control data quality.

🎯 Who Benefits from This Release¶

• Data Engineers: Reusable validation logic and improved control over monitoring behavior
• Data Quality & Governance Teams: Standardized rules and consistent data validation across systems
• Analytics & BI Teams: Better understanding of trends and deviations
• Platform Owners: Increased adoption through simplified analytics and scalable validation

🛠 CLI Updates¶

• No changes