OpenDQ Reviews & Ratings

OpenDQ

5.0 out of 5 stars

Ratings and Reviews 1 Rating

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features 5 out of 5 stars
design 5 out of 5 stars
support 4 out of 5 stars

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What is OpenDQ?

OpenDQ offers an enterprise solution for data quality, master data management, and governance at no cost. Its modular architecture allows it to adapt and expand according to the specific needs of your organization's data management strategies. By leveraging a framework powered by machine learning and artificial intelligence, OpenDQ ensures the reliability of your data. The platform encompasses a wide range of features, including: - Thorough Data Quality Assurance - Advanced Matching Capabilities - In-depth Data Profiling - Standardization for Data and Addresses - Master Data Management Solutions - A Comprehensive 360-Degree View of Customer Information - Robust Data Governance - An Extensive Business Glossary - Effective Meta Data Management This makes OpenDQ a versatile choice for enterprises striving to enhance their data handling processes.

What is Data Quality on Demand?

Data plays a vital role in multiple sectors of a business, such as sales, marketing, and finance. To fully leverage this data, it's important to maintain its integrity, protect it, and manage it effectively throughout its entire lifecycle. At Uniserv, we believe that data quality is a core principle of our identity and the services we offer. Our customized solutions convert your customer master data into a crucial asset for your business. The Data Quality Service Hub ensures that your customer data remains of the highest quality across all locations within your organization, including those overseas. We offer services that align your address information with international standards, utilizing the best reference data available. Furthermore, we validate email addresses, phone numbers, and banking information with meticulous attention to detail. If your data has duplicate entries, we can quickly pinpoint them according to your defined business requirements. Often, the identified duplicates can be merged automatically using predefined rules or categorized for manual assessment, which promotes an efficient data management workflow that boosts operational productivity. This thorough strategy for ensuring data quality not only aids in compliance but also builds trust and credibility in your customer relationships, ultimately leading to stronger business outcomes. An unwavering commitment to data quality fosters a culture of accountability within the organization, encouraging all departments to prioritize accurate data handling.

Media

Media

Integrations Supported

Amazon Kinesis
Amazon S3
Apache Cassandra
Apache HBase
Apache Kafka
Apache Solr
Atom
Azure API Management
Elasticsearch
Google Analytics
Google Calendar
Google Cloud BigQuery
Microsoft Entra ID
MongoDB

Integrations Supported

SAP Store

API Availability

API Availability

Pricing Information

$0
License Free Software
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Infosolve Technologies, Inc

Date Founded

2003

Company Location

United States

Company Website

www.infosolvetech.com

Company Facts

Organization Name

Uniserv

Date Founded

1969

Company Location

Germany

Company Website

www.uniserv.com/en/business-cases/customer-data-management/data-quality/

Categories and Features

Customer Data Platforms (CDP)

Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Process Management
Roles Management

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

Master Data Management

Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization

Categories and Features

Data Quality

Data Deduplication

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