The digna Release 2026.04 takes a major step forward in making data understanding and data quality truly accessible across the enterprise. 

This release significantly expands digna’s capabilities in data analytics and validation, introducing advanced time-series analysis, reusable validation components, and centralized data standardization — all designed to help teams not only detect issues, but understand and control their data with greater precision. 

Making Advanced Data Analysis Accessible 

One of the biggest challenges in modern data environments is not collecting data, it’s understanding how that data behaves over time. 

With Release 2026.04, digna introduces a powerful new Analytics Chart, enabling interactive time-series analysis directly within the platform - without the need for data science tools or programming expertise. 

This allows business users, analysts, and engineers alike to explore data behavior in a structured, intuitive way. 

The New Analytics Capabilities 

At the core of this release is a new set of built-in analytical methods designed to help teams uncover patterns, trends, and deviations in their data: 

• Linear, quadratic, and cubic regression for trend analysis 

• Piecewise regression with configurable breakpoints 

• Smoothing techniques for noise reduction 

• Quantile analysis for distribution insights 

• Residual analysis for deeper anomaly investigation 

In addition, digna automatically generates time-series for every dataset, enabling continuous visibility into how data evolves over time. 

This brings advanced analytical capabilities directly into everyday workflows without requiring external tools or specialized expertise. 

From Monitoring Data to Understanding It 

Traditional data monitoring answers one question: Is something wrong? 

With the new analytics capabilities, digna helps answer a much more important one: 

👉 Why is it happening — and is it expected? 

The platform now automatically identifies: 

• Trends and long-term changes 

• Seasonal patterns and recurring behaviors 

• Structural shifts in data behavior 

• Deviations from expected patterns 

This shift from static monitoring to behavioral understanding enables faster, more confident decision-making across teams. 

Scalable Data Validation Through Reuse and Standardization 

Alongside analytics, Release 2026.04 introduces major improvements in how data validation is defined, reused, and managed across the organization. 

Enumerations — Central Definition of Allowed Values 

Teams can now define reusable sets of allowed values (such as country codes, status values, or categories) and apply them consistently across datasets. 

• Reusable across projects and data sources 

• Defined once, applied everywhere 

• Referenced easily via #ENUM:MY_ENUM# 

All checks are executed directly inside the source database, ensuring performance and zero data movement. 

Validation Rule Templates — Reusable Data Quality Logic 

Validation rules can now be defined as reusable templates and applied across multiple datasets. 

This enables: 

• Consistent validation logic across projects 

• Reduced duplication and manual configuration 

• Faster implementation of data quality checks 

As with all validation in digna, these checks run directly within the source database, supporting scalable and high-performance validation. 

More Precise Monitoring with Relevance Conditions 

Release 2026.04 also extends the concept of anomaly relevance with statistic-level relevance conditions. 

This allows teams to define when a specific metric should be considered relevant for evaluation. 

The result: 

• Reduced alert noise 

• More meaningful signals 

• Monitoring that reflects real business context 

Who Benefits from This Release 

Release 2026.04 brings value across multiple roles: 

• Data Engineers gain reusable validation logic and improved control over monitoring behavior 

• Data Quality & Governance Teams benefit from standardized rules and consistent validation 

• Analytics & BI Teams can now explore trends and deviations without relying on external tools 

• Platform Owners enable broader adoption through simplified analytics and scalable validation 

Built for Modern Data Environments 

With this release, digna continues its focus on in-database processing, ensuring that: 

• Data never needs to be moved for analysis or validation 

• Performance remains high at scale 

• Security and compliance requirements are preserved 

By combining advanced analytics with scalable validation, digna enables organizations to move beyond reactive monitoring toward proactive data understanding and control. 

Explore the Full Release 

Read the full changelog and documentation here 👉 

https://docs.digna.ai/changelog/Release_202604/ 

Release 2026.04 represents another step in digna’s mission to make enterprise data reliable, understandable, and actionable. 

By bringing time-series analytics and reusable validation directly into the platform, we’re helping organizations turn data into insight — without complexity.