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What is iceDQ?

iCEDQ is a comprehensive DataOps platform that specializes in monitoring and testing various data processes. This agile rules engine automates essential tasks such as ETL Testing, Data Migration Testing, and Big Data Testing, which ultimately enhances productivity while significantly shortening project timelines for both data warehouses and ETL initiatives. It enables users to identify data-related issues in their Data Warehouse, Big Data, and Data Migration Projects effectively. By transforming the testing landscape, the iCEDQ platform automates the entire process from beginning to end, allowing users to concentrate on analyzing and resolving issues without distraction. The inaugural version of iCEDQ was crafted to validate and test any data volume utilizing its advanced in-memory engine, which is capable of executing complex validations with SQL and Groovy. It is particularly optimized for Data Warehouse Testing, scaling efficiently based on the server's core count, and boasts a performance that is five times faster than the standard edition. Additionally, the platform's intuitive design empowers teams to quickly adapt and respond to data challenges as they arise.

What is Swan Data Migration?

Our advanced data migration solution is designed with precision to facilitate the smooth transfer and conversion of data from obsolete legacy systems to contemporary frameworks, incorporating comprehensive data validation methods and real-time reporting features. Throughout the data migration process, there is a risk of losing or compromising vital information, which can pose serious challenges. The shift from older systems to newer platforms is often complex and time-consuming. Although it may be tempting to cut corners or to combine data without the appropriate tools, such tactics frequently result in costly and prolonged difficulties. For organizations like State Agencies, the potential for errors during the initial transfer is too significant to overlook. This phase is notoriously challenging, and many organizations find it hard to navigate successfully. A successful data migration effort is heavily contingent on a well-structured initial design that acts as the foundation for the entire project. This crucial stage includes the meticulous development and coding of rules necessary to process different data types tailored to your specific needs, thereby promoting a more efficient migration process. Ultimately, dedicating adequate time and resources in this phase is an investment that can dramatically improve the overall effectiveness and precision of the migration effort, leading to better outcomes for the organization. By prioritizing a thoughtful approach, businesses can ensure a smoother transition that minimizes disruptions and enhances data integrity.

Media

Media

Integrations Supported

Cloudera
Jenkins

Integrations Supported

Cloudera
Jenkins

API Availability

Has API

API Availability

Has API

Pricing Information

$1000
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Torana

Date Founded

2008

Company Location

United States

Company Website

icedq.com

Company Facts

Organization Name

Pritna

Date Founded

2015

Company Location

United States

Company Website

pritna.com/products/data-migration-tool/

Categories and Features

Automated Testing

Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance

Big Data

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

Data Quality

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

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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