QDeFuZZiner - fuzzy data matching, merging & de-duplication software
ABOUT
QDeFuZZiner is a powerful, yet intuitive fuzzy data matching, record linkage and data deduplication 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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INTRODUCTION
Availability of a reliable master data for a supply chain can be crucial for success of a company. Supply chain performance is dependent on consistent definitions of customers, products, items, locations, and other master data objects. When data is poorly governed and inconsistent, supply chains become less competitive. Good data leads to efficient supply chains, allowing resources to be spent on innovation rather than on coping with problems.
However, business data is often messy, containing duplicate entries of same entities, missing information, having misspellings and various other errors.
In many cases, there is no unique identifier which can be used to unambiguously identify an entity. When such data sources need to be linked or deduplicated solely based on string similarity, it is called fuzzy data matching.
Our fuzzy data matching services can help you to consolidate your product and customer master data, by identifying duplicate or linked records, even if lacking unique key identifier.
OUR FUZZY MATCH SOFTWARE
More info about QDeFuZZiner fuzzy matching software:
https://matasoft.hr/QTrendControl/index.php/qdefuzziner-fuzzy-data-matching-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.
Record Linkage
Link and merge related records
Record linkage is the process of bringing together two or more records relating to the same entity (e.g. person, company, product, movie, book, family, event, community, business, hospital, or geographical area).
QDeFuZZiner software can identify and link together same entities, such as same customers or products, from two different datasets.
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QDeFuZZiner can help you to merge and consolidate product and customer lists, from multiple sources.
Duplicate Records Identification
Cleanse your master data
QDeFuZZiner software can identify whether you have the same persons, companies or products registered multiple times in your datasets.
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Our software can help you to consolidate your product lists, customer lists or any other messy datasets, by identifying duplicate records.
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By using QDeFuZZiner, you can perform data cleaning of your messy datasets.
Entity Resolution
Consolidate your customers data
Within the financial, education, healthcare, government, retail, and marketing industries, customer data is vital to business success.
By using QDeFuZZiner, you can minimize duplicate customer data and accurately link each data record to one customer identity.
Fuzzy Data Match Software
Unique fuzzy data matching, record linkage and data deduplication software
By combining intuitive and interactive graphical user interface with clever blocking techniques and powerful string similarity metrics, our fuzzy data match software provides unique and superb tool for performing records matching and data deduplication tasks.
See more about QDeFuZZiner software here: https://matasoft.hr/QTrendControl/index.php/qdefuzziner-fuzzy-data-matching-software
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Want to learn more about our services? Contact us today.