Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Enhance your customer data within a user-friendly environment by easily exporting it into Microsoft Excel and utilizing our plugin, which can be found in the Office Store for improved data quality. With our tool, you can transform data by abbreviating, elaborating, excluding, or normalizing it across five spoken languages and twelve distinct entity categories. You can assess the similarity between records through various comparison techniques, such as Levenshtein and Jaro-Winkler, and generate phonetic match keys for deduplication purposes, including DQ Fonetix™, Soundex, and Metaphone. Additionally, classify your data to determine what each piece represents—for instance, recognizing Brian or Sven as personal names, while identifying Road, Strasse, or Rue as elements of an address, and Ltd or LLC as legal suffixes for companies. You can also derive information such as gender from names and categorize contact information based on job titles and decision-making roles. DQ for Excel™ operates seamlessly within Microsoft Excel, making it both intuitive and straightforward to use, thus streamlining your data management processes effectively. Moreover, with its powerful features, you can ensure that your customer data remains accurate, relevant, and organized.
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
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Microsoft Excel
Palantir Apollo
SolrCommerce
Tableau
Integrations
ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Microsoft Excel
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
DQ Global
Founded
1997
Country
United States
Website
www.dqglobal.com/products/dq-for-excel/
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