Parsed Name Match

Taraf Interzoid | Güncelleyen il y a 2 mois | Data
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Inconsistent, redundant data is often at the root of an organization’s data challenges, causing inaccurate data analysis, faulty decision-making, data management issues, inefficient business processes and other complications that result in increased cost and missed opportunities. Fortunately, using Interzoid’s various data matching APIs and similarity key technology, these challenges can be greatly simplified, if not solved entirely.

Interzoid’s data-specific Data Matching APIs enable a hash-based “similarity key” to be algorithmically generated by traversing similarity trees that have been creating utilizing heuristics, phonetics, specific language knowledge, spelling variation analysis, AI-based learning methods, and rich data-specific reference databases. These similarity keys are then used as the basis of all data matching, enabling variations of similar data, such as “Jim” and “James”, “Street” and “St”, and “Inc.” and “Incorporated” to be identified across data fields. The similarity key approach allows ultimate flexibility in terms of how identified matches are dealt with and for easy integration into a wide range of data-driven applications.

With the Interzoid Matching APIs, you can:

✔ Eliminate redundant and duplicate data from customer and important databases
✔ Leverage data content-specific matching algorithms for higher matching success rates
✔ Improve the accuracy of data analysis activities with better, more accurate foundational data
✔ Utilize fuzzy matching to match data across datasets
✔ Enable fuzzy searching for better, more comprehensive search results
✔ Achieve greater ROI with business intelligence investments
✔ Leverage growing AI-based knowledge bases of matching and ambiguous data identification
✔ Reduce costs associated with redundant, duplicate data
✔ API-based solution enables full customization of data matching strategies
✔ Similarity keys easily are leveraged within a broad range of applications
✔ Easy to get up-and-running with immediate results

Example Results:

First Name, Last Name -> Similarity Key
James,Kelly -> N1Ai4RfV0SRJf2dJwDO0Cvzh4xCgQG
Jim,Kelley -> N1Ai4RfV0SRJf2dJwDO0Cvzh4xCgQG
Jim,Kellie -> N1Ai4RfV0SRJf2dJwDO0Cvzh4xCgQG
Wanda,Curtis -> LV0Tz8hjbfKWiljOpBUK0FjkcRKhz0SJb
Sally,Anderson -> xE5Y6ImDHMQUX6EMlBHD9H17SAoTamH6zCBjFm1
Pau,Mayfield -> BZ6nRf6RCPXSmrZOp8FKRSjQuRvfzOsJY
Sallie,Andersen -> xE5Y6ImDHMQUX6EMlBHD9H17SAoTamH6zCBjFm1

**Input Parameters: **
First name: Person’s first name such as Robert, Jennifer, or Phil
Last name: Person’s last name such as Miller, Jones, or Smith

**Output Parameters: **
SimKey: Generated similarity key used for matching and comparing with other data

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