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What is QDeFuZZiner?

In the QDeFuZZiner application, the core organizational element is termed a project, which includes the definitions of two datasets intended for import and analysis, identified as the "left dataset" and the "right dataset." Each project contains these datasets along with a variable number of solutions that outline the procedures for performing fuzzy match analysis. When a project is created, it is assigned a unique project tag that is then added to the names of the input tables during the raw data importation process. This tagging mechanism ensures the distinctiveness of the imported tables by linking them to their corresponding project names. Additionally, throughout the import process and in subsequent steps for generating and implementing solutions, QDeFuZZiner constructs several indexes within the PostgreSQL database, which improves the effectiveness of fuzzy data matching tasks. The datasets can originate from various spreadsheet formats such as .xlsx, .xls, .ods, or from CSV (comma-separated values) files, which are uploaded to the server database, facilitating the creation, indexing, and processing of the associated left and right database tables. This organized methodology not only enhances data management but also optimizes the analytical process, allowing users to efficiently extract valuable insights from their datasets. Ultimately, this design aims to provide a seamless experience for users, ensuring that they can easily navigate complex data environments.

What is Match2Lists?

Match2Lists delivers the fastest, easiest, and most accurate method for aligning, consolidating, and eliminating duplicate entries in your data. Utilizing our Match2D&B feature, you can effortlessly enrich your datasets with Dun & Bradstreet information whenever necessary. In just minutes, you can cleanse your data of duplicates and transform varied raw data into valuable insights. Our main objective is to achieve the best possible matching results for our clients. Prior to launching Match2Lists, we ran analytics and data visualization companies, using several "fuzzy" matching tools available in the market. Disappointed with their poor matching performance, we spent a decade developing the most advanced algorithms for data matching. Additionally, we strive to enhance efficiency: our aim is to enable clients to spend less time on data matching and cleansing, allowing them to concentrate on analysis and implementation. This commitment drove us to deploy our innovative matching logic on the most rapid in-memory cloud computing infrastructure we could secure, capable of processing 200 million records in merely 30 seconds. As a result, organizations can boost productivity and make quick, informed decisions, ultimately transforming their data management approach. Now, they can leverage these improvements to drive growth and success in their respective industries.

Media

Media

Integrations Supported

PostgreSQL

Integrations Supported

PostgreSQL

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$95 per month
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

QDeFuZZiner

Company Website

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

Company Facts

Organization Name

Match2Lists

Company Location

United Kingdom

Company Website

www.match2lists.com

Categories and Features

Categories and Features

Popular Alternatives

Popular Alternatives

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