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Description
digna is a next-generation European data quality and observability platform that empowers organizations to improve data trust, reduce downtime, and uncover actionable insights.
Its five independent modules — Data Anomalies, Data Analytics, Data Timeliness, Data Validation, and Data Schema Tracker — address both data quality and operational/business monitoring. From detecting unexpected drops in record counts to spotting surges in product sales, digna gives you visibility across your entire data ecosystem.
Key advantages:
• In-database processing for full privacy & compliance
• AI-powered anomaly detection with zero manual rules
• Business trend analysis through statistical insights
• Regulatory compliance with flexible validation rules
• Pipeline protection via schema change tracking
Trusted in finance, healthcare, telecom, and government, digna integrates seamlessly with Snowflake, Databricks, Teradata, and more — whether on-premises, in the cloud, or hybrid.
With digna, your data is not just monitored — it’s understood.
Use Cases
Banking & Finance – Detect unusual spikes in transaction volumes to ensure both regulatory compliance and fraud prevention.
Healthcare – Monitor data timeliness to guarantee patient records and lab results arrive on time for critical decision-making.
Retail & eCommerce – Track sales trends and product anomalies to quickly identify fast-moving or underperforming items.
Telecommunications – Prevent schema drift in massive customer databases to avoid broken pipelines and billing errors.
Description
In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.
API Access
Has API
API Access
Has API
Integrations
MySQL
SQL Server
Snowflake
Amazon Redshift
ClickHouse
Gmail
Google Cloud BigQuery
IBM Netezza Performance Server
Looker
MariaDB
Integrations
MySQL
SQL Server
Snowflake
Amazon Redshift
ClickHouse
Gmail
Google Cloud BigQuery
IBM Netezza Performance Server
Looker
MariaDB
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$825 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
digna GmbH
Founded
2019
Country
Austria
Website
www.digna.ai
Vendor Details
Company Name
Metaplane
Country
United States
Website
www.metaplane.dev/
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Product Features
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management