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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

iceDQ, a DataOps platform that allows monitoring and testing, is a DataOps platform. iceDQ is an agile rules engine that automates ETL Testing, Data Migration Testing and Big Data Testing. It increases productivity and reduces project timelines for testing data warehouses and ETL projects. Identify data problems in your Data Warehouse, Big Data, and Data Migration Projects. The iceDQ platform can transform your ETL or Data Warehouse Testing landscape. It automates it from end to end, allowing the user to focus on analyzing the issues and fixing them. The first edition of iceDQ was designed to validate and test any volume of data with our in-memory engine. It can perform complex validation using SQL and Groovy. It is optimized for Data Warehouse Testing. It scales based upon the number of cores on a server and is 5X faster that the standard edition.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Cloudera No 
IBM Netezza Performance Server Yes 
Jenkins No 
MariaDB Yes 
MySQL Yes 
PostgreSQL Maestro Yes 
SAP HANA Yes 
SQL Server Yes 
Snowflake Yes 

Integrations

Cloudera Yes 
IBM Netezza Performance Server No 
Jenkins Yes 
MariaDB No 
MySQL No 
PostgreSQL Maestro No 
SAP HANA No 
SQL Server No 
Snowflake No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$1000
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

digna GmbH

Founded

2019

Country

Austria

Website

www.digna.ai

Vendor Details

Company Name

iceDQ

Founded

2005

Country

United States

Website

icedq.com

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

Data Quality

Address Validation Yes 
Data Deduplication Yes 
Data Discovery Yes 
Data Profililng Yes 
Master Data Management Yes 
Match & Merge Yes 
Metadata Management Yes 

Product Features

Automated Testing

Hierarchical View No 
Move & Copy Yes 
Parameterized Testing Yes 
Requirements-Based Testing Yes 
Security Testing No 
Supports Parallel Execution Yes 
Test Script Reviews No 
Unicode Compliance No 

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Alternatives

Alternatives

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