Game Changer: Demyst’s Entity Resolution Tech

External data supply is exploding, but its viability as an insight generation mechanism is limited by the fragmented and opaque nature of the marketplace as well as the complexities involved in ensuring accuracy during acquisition and integration. 

The Need for an Entity Resolution Partner 

Data providers specialize in collecting and organizing a diverse range of data across multiple entity types. Unfortunately, these providers often specialize in details that serve different sections of the market, which can lead to gaps and inaccuracies when handling information outside of their areas of expertise.

Although it’s possible to fill in the gaps by consulting multiple data sources — it can be difficult to link known details with potential information about specific entities. This leaves enterprises with the headache of identifying and integrating valid data into their own workflows.

To circumvent this cost prohibitive, time consuming, and laborious process, enterprises should leverage the expertise of an external data specialist to automate the verification process and manage the cost of data optimization. 

External data specialists employ entity resolution to accomplish these results. 

What is Entity Resolution? 

Entity resolution is a three-part process in which disparate data points relating to an entity (such as a person, business, or property) are pulled from multiple databases, validated for accuracy, and collated under one normalized label. 

Imagine for a moment that three specialty data sources each house the phone number, home address, and place of employment pertaining to an individual by the name of Michael Customer, in addition to high value source-specific attributes. Each of the aforementioned non-exclusive data points are correct and are an exact match with that of the other sources, with one exception. The name listed in each source: M. Customer, Michelle Customer, and Mikey Customer, do not match the name of the entity, Michael Customer, or one another. 

An organization that has access to the three sources mentioned above, can pull the data, determine that three of the four aforementioned data points match each other as well as those listed in an internal reference file, and consolidate the acquired information into a dataset with the entity’s accurate name, which is listed in the reference file. 

Thanks to entity resolution, said organization now has a cohesive view of Michael Customer that contains all of the high value attributes in one location — enabling insight generation and data-driven business decisions.

Demyst’s Dynamic Entity Resolution 

Demyst has developed a custom entity resolution algorithm that accomplishes these results automatically and at massive scale.

The in-house technology continuously collects, verifies, and updates data from the hundreds of data products in the Demyst ecosystem, ensuring that internal Demyst reference files are a source of truth. When an API is queried in the Demyst platform, the algorithm selects optimal matches against internal reference files and provides confidence scores to assess the accuracy of the qualified match. 

Demyst enables users to choose their confidence score when bringing an API into production — there is a high level of flexibility. Users who wish to cast a wide net can maximize fill rate by lowering their confidence level while those that require a tighter level of accuracy can increase the threshold. 

Demyst Makes it Simple

An external data specialist, Demyst delivers end-to-end value via its proprietary entity resolution technology and vast ecosystem of external data sources. 

By partnering with Demyst, enterprises outsource the work of verifying results, managing the costs of data optimization, and adapting to ongoing changes in the ever evolving data landscape.

This partnership converts data into consistent formats that suit enterprises’ existing workflows, resulting in improved business outcomes and compliance results.

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