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Average Ratings 0 Ratings
Description
The DataMatch Enterprise™ solution is an intuitive data cleansing tool tailored to address issues related to the quality of customer and contact information. It utilizes a combination of unique and standard algorithms to detect variations that are phonetic, fuzzy, miskeyed, abbreviated, and specific to certain domains. Users can establish scalable configurations for various processes including deduplication, record linkage, data suppression, enhancement, extraction, and the standardization of both business and customer data. This functionality helps organizations create a unified Single Source of Truth, thereby enhancing the overall effectiveness of their data throughout the enterprise while ensuring that the integrity of the data is maintained. Ultimately, this solution empowers businesses to make more informed decisions based on accurate and reliable data.
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
No
API Access
Has API
No
Integrations
Act!
Yes
Bullhorn
Yes
Eloqua
Yes
Google Ads
Yes
Google Analytics
Yes
Highrise
Yes
HubSpot CRM
Yes
Magento
Yes
Mailchimp
Yes
NetSuite
Yes
Integrations
Act!
No
Bullhorn
No
Eloqua
No
Google Ads
No
Google Analytics
No
Highrise
No
HubSpot CRM
No
Magento
No
Mailchimp
No
NetSuite
No
Pricing Details
No price information available.
Free Trial
No
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
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
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
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
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Data Ladder
Founded
2006
Country
United States
Website
dataladder.com
Vendor Details
Company Name
QDeFuZZiner
Website
zmatasoft.wixsite.com/qdefuzziner/qdefuzziner-software-features
Product Features
Address Verification
Address Validation
No
Autocomplete
No
Automatic Formatting
No
Data Cleansing
No
Data Discovery
No
Data Quality Control
No
Data Verification
No
Geographic Maps
No
Geolocation
No
Metadata Management
No
Reporting / Analytics
No
Search / Filter
No
Data Quality
Address Validation
No
Data Deduplication
Yes
Data Discovery
No
Data Profililng
No
Master Data Management
No
Match & Merge
Yes
Metadata Management
No