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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

ON EBX is a multi-domain master data management platform designed to help enterprises organize, govern, and maintain consistent information across complex data environments. The software consolidates master data, reference data, and metadata from fragmented systems into a centralized foundation for business operations, analytics, and AI applications. Its model-driven architecture enables organizations to create and modify data structures without being restricted to rigid, predefined data models. Built-in data quality capabilities use validation rules, governance workflows, and lifecycle controls to improve accuracy and reduce manual reconciliation. ON EBX also enriches enterprise information with relationships, hierarchies, and business rules that provide additional context for downstream applications. Customer 360 capabilities help organizations establish consistent customer records and improve visibility across business functions. Product and supplier data management features support accurate product information, supplier governance, and coordination across enterprise processes. Reference data management helps standardize shared classifications, codes, and other common information used by multiple systems. ON EBX supports financial services, healthcare, retail, manufacturing, and other data-intensive industries that require governed enterprise information for operational efficiency, regulatory oversight, analytics, and AI initiatives.

Description

Zingg is an open-source platform designed for Master Data Management, tailored for contemporary data warehousing needs. By leveraging machine learning for scalable entity resolution, it removes the reliance on costly and inflexible MDM solutions. Seamlessly integrated with Databricks, Microsoft Fabric, Snowflake, AWS, and GCP, Zingg empowers data teams to create a cohesive and reliable view of customers, suppliers, and products directly within their existing data environments. With a persistent Zingg ID, golden records are consistently upheld across various systems and data sources, ensuring data integrity and accessibility. Moreover, Zingg's innovative approach simplifies the management of master data, allowing organizations to focus on data-driven decision-making.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

No images available

Integrations

Amazon Web Services (AWS) No 
Databricks No 
Google Cloud Platform No 
Microsoft Fabric No 
Snowflake No 

Integrations

Amazon Web Services (AWS) Yes 
Databricks Yes 
Google Cloud Platform Yes 
Microsoft Fabric Yes 
Snowflake Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Contact For Pricing
Free Trial No 
Free Version Yes 

Deployment

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Cloud Software Group

Country

United States

Website

www.onebx.com

Vendor Details

Company Name

Zingg Labs, Inc

Founded

2021

Country

United States

Website

www.zingg.ai/

Product Features

Data Governance

Access Control No 
Data Discovery No 
Data Mapping No 
Data Profiling No 
Deletion Management No 
Email Management No 
Policy Management No 
Process Management No 
Roles Management No 
Storage Management No 

Data Lineage

Database Change Impact Analysis No 
Filter Lineage Links No 
Implicit Connection Discovery No 
Lineage Object Filtering No 
Object Lineage Tracing No 
Point-in-Time Visibility No 
User/Client/Target Connection Visibility No 
Visual & Text Lineage View No 

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

Master Data Management

Data Governance No 
Data Masking No 
Data Source Integrations No 
Hierarchy Management No 
Match & Merge No 
Metadata Management No 
Multi-Domain No 
Process Management No 
Relationship Mapping No 
Visualization No 

Product Features

Master Data Management

Data Governance Yes 
Data Masking No 
Data Source Integrations Yes 
Hierarchy Management Yes 
Match & Merge Yes 
Metadata Management Yes 
Multi-Domain Yes 
Process Management Yes 
Relationship Mapping Yes 
Visualization Yes 

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