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Description

Data cleansing, migration, integration, and reconciliation can occur seamlessly between cloud environments and on-premise systems. Operating on OCI, it provides secure connectivity to Oracle Enterprise Applications whether hosted in the cloud or on-premises. This unified platform facilitates data and setup migrations, integrations, reconciliations, big data ingestion, and archival processes. It boasts over 9,000 pre-built API templates and web services for enhanced functionality. The data quality engine incorporates pre-configured business rules to efficiently profile, clean, enrich, and correct data, ensuring high standards are maintained. With its configurable, agile design, it supports both low-code and no-code environments, allowing for immediate utilization in a fully cloud-enabled context. This migration platform is specifically designed for transferring data into Oracle Cloud Applications, Oracle E-Business Suite, Oracle JD Edwards, Microsoft Dynamics, Oracle Peoplesoft, and numerous other enterprise applications, accommodating a range of legacy systems as well. Its robust and scalable framework is complemented by a user-friendly interface, while more than 3,000 Smart Data Adapters are available, providing comprehensive coverage for various Oracle Applications and enhancing the overall migration experience.

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 
Jenkins No 

Integrations

Cloudera Yes 
Jenkins Yes 

Pricing Details

No price information available.
Free Trial Yes 
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 Yes 
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 No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

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

Vendor Details

Company Name

ChainSys

Founded

1998

Country

United States

Website

www.chainsys.com

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 

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 

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 

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