Actian Data ObservabilityActian
|
Dignadigna GmbH
|
|||||
Related Products
|
||||||
About
Actian Data Observability is an AI-powered platform designed to continuously monitor, validate, and manage the health, quality, and reliability of data across modern data environments. It uses automated Data Observability Agents that validate data as it arrives in data lakehouses or warehouses, detecting anomalies, explaining root causes, and coordinating resolution before issues impact dashboards, reports, or AI systems. It provides real-time visibility into data pipelines, ensuring that data remains accurate, complete, and trustworthy throughout its lifecycle. It eliminates blind spots by monitoring 100% of data rather than relying on sampling, allowing organizations to identify hidden errors that could otherwise corrupt analytics or machine learning outcomes. With built-in anomaly detection powered by AI and machine learning, it proactively identifies irregularities such as schema changes, missing data, or unexpected distributions, enabling faster diagnosis and resolution.
|
About
digna is a data quality and observability platform designed to monitor, analyze, and validate data directly within enterprise data environments.
It combines anomaly detection, time-series analytics, and validation into a unified system that helps teams detect issues early and understand how data behaves over time.
Core Capabilities
* Data Anomaly Detection
Identifies changes in data volume, distribution, and behavior using statistical methods and AI-driven models without relying on manually defined rules.
* Time-Series Analytics
Built-in analytical methods (regression, pattern detection, seasonality analysis) allow users to interpret trends and deviations directly within the platform.
* Data Timeliness Monitoring
Tracks expected data arrival times and identifies delays across pipelines and data flows.
* Data Validation
Supports rule-based validation with reusable templates and centralized definitions of allowed values.
* Schema Change Tracking
Detects structural changes in dat
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Data engineers and analytics teams who need to proactively monitor and ensure data quality across pipelines to support reliable AI and business decisions
|
Audience
Data warehouses, data lakes, data lakehouses, banks, retail, hospitals
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationActian
Founded: 1980
United States
www.actian.com/data-observability/
|
Company Informationdigna GmbH
Founded: 2019
Austria
www.digna.ai
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
Categories |
Categories |
|||||
Data Quality Features
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
|
||||||
Integrations
SQL Server
Snowflake
Amazon Redshift
Amazon S3
Amazon Web Services (AWS)
Apache Iceberg
Databricks
Delta Lake
Google Analytics
Google Cloud BigQuery
|
Integrations
SQL Server
Snowflake
Amazon Redshift
Amazon S3
Amazon Web Services (AWS)
Apache Iceberg
Databricks
Delta Lake
Google Analytics
Google Cloud BigQuery
|
|||||
|
|
|