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Average Ratings 0 Ratings

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ease
features
design
support

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Description

MatchX offers a comprehensive AI-enhanced data quality and matching solution that revolutionizes how companies manage their information assets. By integrating powerful data ingestion capabilities and intelligent schema mapping, MatchX structures and validates data from diverse sources, including APIs, databases, and documents. The platform’s self-learning AI models automatically detect and correct inconsistencies, duplicates, and anomalies, ensuring data integrity without intensive manual intervention. MatchX also provides advanced entity resolution techniques like phonetic and semantic matching to unify records with high precision. Its role-based workflows and audit trails facilitate compliance and governance across industries. Real-time AI-driven dashboards deliver continuous monitoring of data quality, trends, and compliance status. This end-to-end automation enhances operational efficiency while reducing risks associated with poor data. Built to handle massive data volumes, MatchX scales effortlessly with evolving business demands.

Description

In QDeFuZZiner software, the fundamental unit is referred to as a project, which encompasses the definitions of two source datasets for import and analysis, known as the "left dataset" and "right dataset." Each project not only includes these datasets but also a variable number of solutions that detail the methodology for conducting fuzzy match analysis. Upon creation, every project is assigned a distinct project tag, which is subsequently appended to the names of the corresponding input tables during the raw data import process. This tagging system guarantees that the imported tables maintain uniqueness through association with their respective project names. Furthermore, during the import phase and later when generating and executing solutions, QDeFuZZiner establishes various indexes on the PostgreSQL database, thereby enhancing the efficiency of fuzzy data matching procedures. The datasets themselves can be sourced from spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma separated values) flat files, which are uploaded to the server database, leading to the creation, indexing, and processing of the associated left and right database tables. This structured approach not only simplifies data management but also streamlines the analysis process, making it easier for users to derive insights from their datasets.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

PostgreSQL Yes 
Apache Kafka Yes 
Collibra Yes 
Looker Yes 
Microsoft Power BI Yes 
Salesforce Yes 
Tableau Yes 

Integrations

PostgreSQL Yes 
Apache Kafka No 
Collibra No 
Looker No 
Microsoft Power BI No 
Salesforce No 
Tableau No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

VE3 Global

Founded

2010

Country

United Kingdom

Website

www.ve3.global/matchx/

Vendor Details

Company Name

QDeFuZZiner

Website

zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features

Product Features

Data Quality

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

Product Features

Alternatives

Alternatives