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What is NetOwl NameMatcher?

NetOwl NameMatcher, celebrated for its superior performance in the MITRE Multicultural Name Matching Challenge, offers exceptional accuracy, rapid processing, and scalability in its name matching solutions. Utilizing a cutting-edge machine learning framework, NetOwl adeptly addresses the complex challenges associated with fuzzy name matching. Traditional techniques like Soundex, edit distance, and rule-based systems frequently struggle with precision, leading to an abundance of false positives, and recall issues that result in false negatives, particularly when faced with the varied fuzzy name matching scenarios mentioned earlier. In contrast, NetOwl adopts a data-driven, machine learning-based probabilistic approach to overcome these name matching challenges effectively. It autonomously develops advanced, probabilistic name matching rules from vast real-world datasets containing multi-ethnic name variants. Additionally, NetOwl implements specialized matching models designed for different entity types, including individuals, organizations, and geographical locations. To enhance its functionality, NetOwl incorporates automatic detection of name ethnicity, which significantly boosts its adaptability to the complexities inherent in multicultural name matching. This holistic strategy not only elevates accuracy but also ensures dependable performance across a wide array of applications. Consequently, organizations relying on precise name matching can greatly benefit from the innovative solutions provided by NetOwl.

What is DataMatch?

The DataMatch Enterpriseâ„¢ solution serves as a user-friendly tool for data cleansing, specifically designed to tackle challenges associated with the quality of customer and contact information. It employs an array of both unique and standard algorithms to identify inconsistencies that may result from phonetic similarities, fuzzy matches, typographical errors, abbreviations, and domain-specific variations. Users have the ability to implement scalable configurations for a variety of processes, including deduplication, record linkage, data suppression, enhancement, extraction, and the standardization of business and customer data. This capability is instrumental in helping organizations achieve a cohesive Single Source of Truth, which significantly boosts the overall effectiveness of their data management practices while safeguarding data integrity. In essence, this solution enables businesses to make strategic decisions rooted in precise and trustworthy data, ultimately fostering a culture of data-driven decision-making across the organization. By ensuring high-quality data, companies can enhance their operational efficiency and drive better customer experiences.

Media

Media

Integrations Supported

ArcGIS
Bullhorn
Eloqua
Google Maps
Highrise
IBM Cloud
Mailchimp
MarkLogic
NetSuite
NetSuite CRM
Oracle CRM On Demand
Palantir Apollo
Salesforce
Salesforce Agentforce Marketing
Sugar Sell
Tableau
Veeva CRM
Zoho CRM
unTill

Integrations Supported

ArcGIS
Bullhorn
Eloqua
Google Maps
Highrise
IBM Cloud
Mailchimp
MarkLogic
NetSuite
NetSuite CRM
Oracle CRM On Demand
Palantir Apollo
Salesforce
Salesforce Agentforce Marketing
Sugar Sell
Tableau
Veeva CRM
Zoho CRM
unTill

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

NetOwl

Date Founded

1996

Company Location

United States

Company Website

www.netowl.com/name-matching-software

Company Facts

Organization Name

Data Ladder

Date Founded

2006

Company Location

United States

Company Website

dataladder.com

Categories and Features

Data Quality

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

Categories and Features

Address Verification

Address Validation
Autocomplete
Automatic Formatting
Data Cleansing
Data Discovery
Data Quality Control
Data Verification
Geographic Maps
Geolocation
Metadata Management
Reporting / Analytics
Search / Filter

Data Quality

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

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