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API StatusChangelog
digna
ByMarcinMarcin

digna

#93in Analytics
Discussions2
Followers2
OverviewDiscussions2

What is digna?

Is the game-changing European modern data quality platform that effortlessly uncovers anomalies and errors in your data with Artificial Intelligence.

digna is a tool in the Analytics category of a tech stack.

Key Features

data validation, BCBS 239 data quality, regulatory data observability, banking data governance, risk reporting data quality, risk aggregation, manipulation anomaly indicators, data lineage insights, data SLA monitoringschema monitoring, schema change detection, new column detection, removed column detection, datatype change detection, schema drift detection, database schema tracking, schema observabilitydata freshness monitoring, data timeliness, late data detection, missing batch detection, data arrival monitoring, delivery timestamp tracking, trigger-based timestamp, SQL-derived timestamp, pipeline latency monitoring, SLA breach alertstimeliness, schema tracker, data analytics, prebuilt data quality rules, 9000+ rules, custom data rules, SQL validation rules, rule engine, conditional data rules, uniqueness checks, range checks, primary key validation, cross-table validation, rule exceptions, severity levelsproject management, trend analysis, time-series analytics, volatility detection, change point detection, long-term data trends, stable dataset detection, unstable dataset detection, pattern recognition, historical data metrics, data profiling analyticsworkspace managementAI anomaly detection, data anomalies, volume anomalies, distribution anomalies, outlier detection, data drift detection, missing values detection, NULL pattern analysis, threshold monitoring, detect data manipulation, early warning signals, automatic anomaly detection, Slack alerts, email alerts, Teams alerts, webhook alerts, role-based access control, RBAC, scheduling inspections, cron scheduling, event-based scheduling, CLI access, API access, SSO integration, OIDC, Microsoft SSO, Google SSO, multi-database connectors, on-prem installation, private cloud installation, secure deployment

digna Pros & Cons

Pros of digna

No pros listed yet.

Cons of digna

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digna Alternatives & Comparisons

What are some alternatives to digna?

Keen

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Ahoy

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Ahoy provides a solid foundation to track visits and events in Ruby, JavaScript, and native apps.

Snowplow

Snowplow

Snowplow is a real-time event data pipeline that lets you track, contextualize, validate and model your customers’ behaviour across your entire digital estate.

Bitdeli

Bitdeli

Build dashboards and reports with exactly the metrics you need using plain Python scripts. There is nothing new to learn. Bitdeli keeps your results up to date, no matter how much data you have or how complex your metrics are. Get started in minutes with our growing library of open-source analytics, created by experienced data hackers.

Open Web Analytics

Open Web Analytics

It is open source web analytics software that you can use to track and analyze how people use your websites and applications. It provides website owners and developers with easy ways to add web analytics to their sites using simple Javascript, PHP, or REST based APIs.

Statsbot

Statsbot

Statsbot is helping you take control of your raw data, providing an all-in-one analysis tool for engineers and non-tech folks alike.

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digna Discussions

Discover why developers choose digna. Read real-world technical decisions and stack choices from the StackShare community.

Marcin Chudeusz
Marcin Chudeusz

Nov 27, 2025

Announcementondignadigna

digna Data Anomalies: https://www.digna.ai/data-anomalies

digna Data Analytics: https://www.digna.ai/data-analytics

digna Data Validation: https://www.digna.ai/data-validation

digna Timeliness: https://www.digna.ai/data-timeliness

digna Schema Tracker: https://www.digna.ai/data-schema-tracker

digna

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Marcin Chudeusz
Marcin Chudeusz

Nov 27, 2025

Announcementondignadigna

digna introduces a fully modular, AI-powered approach that complements Teradata’s architecture without extracting customer data. 

Only metrics are exported — processing happens inside your Teradata system. 

Below are the modules most relevant for enterprise Teradata workloads. 

AI-powered anomaly detection for volumes, distributions, outliers & missing data 

As workloads scale, Teradata tables can shift subtly over time — and without visibility, these issues reach end users or models too late. 

digna Data Anomalies automatically learns: 

When something deviates beyond AI-learned expectations, digna notifies teams before problems escalate. 

Perfect for Teradata environments that: 

This replaces hundreds of static rules with a single AI-powered monitoring layer. 

Long-term trend analysis for observability metrics 

Teradata’s workload patterns evolve over months and quarters. digna Data Analytics evaluates trends over time to detect:

These insights help platform teams:

This is especially impactful in Teradata’s massive, multitenant data environments. 

AI-driven and rule-based monitoring of data arrival times 

SLA breaches are a common pain point in Teradata-powered analytics. 

digna monitors: 

Its AI model learns normal behavior instead of relying purely on a static SLA definition. 

A rule-based layer for strict compliance and audit requirements 

Some industries (finance, insurance, telecommunications, healthcare) require explicit, enforceable rules. 

digna Data Validation provides: 

This complements the AI modules by ensuring that every record meets defined business expectations. 

Protecting pipelines from schema drift 

Teradata environments often support hundreds of pipelines. A single schema change can break dozens of downstream jobs. 

digna automatically tracks: 

When drift occurs, teams are alerted immediately, preventing silent pipeline failures. 

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