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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

DQLabs boasts ten years of expertise in delivering data solutions tailored for Fortune 100 companies, focusing on areas such as data integration, governance, analytics, visualization, and data science. The platform is equipped with comprehensive features that allow for autonomous execution, eliminating the need for manual configurations. Utilizing advanced AI and machine learning technologies, it ensures scalability, governance, and end-to-end automation are seamlessly achieved. Furthermore, it offers straightforward integration with various tools within the data ecosystem. By harnessing AI and machine learning, this innovative platform enhances decision-making across all facets of data management. Gone are the days of cumbersome ETL processes, workflows, and rigid rules; instead, organizations can embrace a new era of AI-driven decision-making that adapts and recalibrates automatically in response to evolving business strategies and emerging data patterns. This adaptability ensures that businesses remain agile and responsive in the ever-changing landscape of data management.

Description

NetOwl NameMatcher, recognized for its excellence in the MITRE Multicultural Name Matching Challenge, delivers unparalleled accuracy, speed, and scalability in name matching solutions. By employing an innovative machine learning framework, NetOwl effectively tackles the intricate challenges of fuzzy name matching. Conventional methods like Soundex, edit distance, and rule-based systems often face significant issues with precision, leading to false positives, and recall, resulting in false negatives, when confronting the diverse fuzzy name matching scenarios outlined previously. In contrast, NetOwl leverages a data-driven, machine learning-based probabilistic strategy to address these name matching difficulties. It automatically generates sophisticated, probabilistic name matching rules from extensive, real-world multi-ethnic name variant datasets. Furthermore, NetOwl employs distinct matching models tailored to various entity types, such as individuals, organizations, and locations. To add to its capabilities, NetOwl also integrates automatic detection of name ethnicity, enhancing its adaptability to the complexities of multicultural name matching. This comprehensive approach ensures a higher level of accuracy and reliability in diverse applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ArcGIS
DataOps.live
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

Integrations

ArcGIS
DataOps.live
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DQLabs, Inc

Country

United States

Website

www.dqlabs.ai/

Vendor Details

Company Name

NetOwl

Founded

1996

Country

United States

Website

www.netowl.com/name-matching-software

Product Features

Data Quality

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

Product Features

Data Quality

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

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