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QDeFuZZiner

- User friendly fuzzy data matching software

2020-06-12 20_10_04-QDeFuZZiner - mataso
ABOUT

QDeFuZZiner is a powerful, yet intuitive fuzzy data matching, matching and data de-duplication software

 

https://matasoft.hr/QTrendControl/index.php/qdefuzziner-fuzzy-data-matching-software

 

#QDeFuZZiner #FuzzyMatching #FuzzyMatch #RecordLinkage #DataScience #String #Data #DataDeduplication #DataDissambiguation #EntityResolution #MDM #MasterData #FuzzyStringMatching #DataConsolidation #MasterDataManagement #ApproximateStringMatching #DataCleaning #DataCleansing

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QDeFuZZiner - MAIN FEATURES

Main features of the QDeFuZZiner software:

  • Robust back-end PostgreSQL database, capable of storing, indexing and processing heavy input datasets

  • Intuitive and interactive front-end desktop GUI application

  • Importing input datasets from spreadsheet and flat (csv) files through interactive GUI

  • Intuitive organization of fuzzy data matching projects

  • Intuitive creation of multiple solutions inside each project

  • Each solution provides interactive user interface for definition of various fuzzy matching parameters (blocking similarity threshold, similarity threshold, optional usage of lexemization and dictionaries)

  • Each solution provides definition of exact matching constraints, fuzzy matching constraints, other constraints

  • You can define merged columns in a resultset, multiple options of merging types are available

  • Graphical tool for visualization of similarity distribution of matches and non-matches in a solution table, providing help in determining otimum threshold value for a solution

  • Interactive datagrids with integrated searching, filtering, sorting and customization capabilities

  • Interactive splitters between form sections, helping in optimum utilization of screen space

  • Integrated spreadsheet software "Spready" for analyzing input datasets and resultsets

  • Integrated Libfreoffice Calc spreadsheet software for analyzing input datasets and resultsets

  • Exporting of resultsets into spreadsheet files (.xlsx, .xls, .ods) or flat files (.csv, .txt, .tab)

  • QDeFuZZiner comes with several demo projects available

OUR FUZZY MATCH SOFTWARE

​There are many business cases where record linkage has to be performed.

Some typical examples are: merging or deduplication of product price lists, partner lists, book and movie catalogs, customer loyalty databases, medical records etc.
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Our data matching software quickly identifies duplicates from your datasets by finding similarities between data elements, such as names and addresses, enabling effective data cleansing.
 
Our powerful fuzzy matching engine identifies linked or similar records that contain keyboard errors, missing words, extra words, nicknames, changed surnames, or multicultural name variations. 

QDeFuZZiner - Projects.png

Managing Fuzzy Matching Projects

Manage record linkage and data deduplication projects

Project is basic entity in QDeFuZZiner software. Each project contains definition of two source datasets to be imported and analyzed (so-called "left dataset" and "right dataset"), as well as variable number of corresponding solutions, which are stored definitions of how to perform fuzzy match analysis.

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On creation, each project is assigned unique project tag. During raw data importing to server, corresponding input tables get that tag appended in their name. This way, imported tables are always tagged by the project name, which ensures their uniqueness.

QDeFuZZiner - Import.png

Importing Input Datasets

Import source datasets in spreadsheet or flat text formats

QDeFuZZiner provides mechanism for importing raw input datasets, in spreadsheet or flat textual files format, into corresponding tables on the PostgreSQL database server.

 

Datasets are  imported from source spreadsheet (.xlsx, .xls, .ods) or CSV (comma separated values) flat files to server database, where corresponding left and right database tables are then created, indexed and processed.

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During importing and also later on, during solutions creation and execution, QDeFuZZiner is creating various indexes on the underlying PostgreSQL database, which facilitate fuzzy data matching.

Want to learn more about our services? Contact us today.

2020-06-12 20_10_04-QDeFuZZiner - mataso

Manage and execute Fuzzy Matching Solutions

Manage multiple fuzzy match solutions for each project

By term "Solution" we consider section of the QDeFuZZiner in which fuzzy matching specification is defined, fuzzy matching execution is performed and results are acquired and manipulated. Solution is the most important object in QDeFuZZiner software. Each solution belongs to a certain project, i.e. one project can contain multiple solutions.

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A solution is an entity on which you define all the parameters that will influence how fuzzy matching will be performed, provide specification of field pairs to be matched, along with exact, fuzzy and other constraints.

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By executing solution specification, fuzzy data matching analysis is executed on the underlying PostgreSQL database. Upon completion of fuzzy matching, retrieved results are saved as new table and presented in a datagrid.

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Retrieved resultset can be exported into a spreadsheet (.xlsx, .xls, .ods) or flat plain text (.csv, .tab, .txt) files and downloaded to your local computer, via FTP.

QDeFuZZiner - Solution Parameters.png

Define Fuzzy Matching Parameters

Define parameters for solution definition

QDeFuZZiner provides intuitive and straight-forward definition of general parameters used for a fuzzy matching solution.

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Define parameters such as blocking similarity limit, similarity threshold and join type.  Define whether solution is related to record linkage or data deduplication fuzzy matching type.

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Optionally, you can utilize lexemization with dictionaries, in order to improve fuzzy match quality.

Return all matching records or only best matching combinations.

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Define exact matching constraints, fuzzy matching constraints, other constraints, merged columns.

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Export fuzzy match results into spreadsheet or plain textual flat files. Search, filter, sort and explore retrieved resultsets.

QDeFuZZiner - Similarity Distribution Es

Visual Similarity Distribution Estimator

QDeFuZZiner - Fields Picker.png

Define Other Custom Constraints

QDeFuZZiner - Exact Matching Constraints

Define Exact Match Constraints

QDeFuZZiner - Merged Columns.png

Define Merged Columns

QDeFuZZiner - Fuzzy Match Constraints.pn

Define Fuzzy Match Constraints

QDeFuZZiner - Fuzzy Match Result.png

Search, Filter, Sort and Export Resultset

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