ADAPT Spin-Out Aims to Make Sense of Disorganised Data

19 January 2021
ADAPT Spin-Out Aims to Make Sense of Disorganised Data

Posted: 14/07/18

An ADAPT spin-out company, Data Chemist, has just raised €1.2 million to fully develop and globally launch its technology.  The technology allows companies to make sense of masses of stored disorganised data. Headed up by former Professors of the School of Computer Science and Statistics at Trinity College Dublin Dr Kevin Feeney and Dr Gavin Mendelsen, the company originated out of a €4 million EU-funded international research project on data quality and is supported by Atlantic Bridge University Bridge Fund and Enterprise Ireland.

The company’s product of the same title, is a ground-breaking data analytics software that allows for identification of patterns and relationships between factors beyond the limitations of a traditional Relational or Graph database. Though these two models are still frequently used to manage data, they are not properly equipped for handling complex inquiries concerning the relationships between entities of interest.

Speaking about the concept Dr Feeney compares the Relational Model with filing data as opposed to scrutinising the connections between them. “The new questions are about investigation. Which other products are typically bought by users who bought this product? Is this specific individual related to this particular company in any way – even indirectly? What is the shortest route connecting these 15 physical locations on the map?” he explains.

The Graph database, though more focused on organising data according to entities and the relationships between them, is often used solely by data analysts to explore existing data sets, and is limited by its capacity for adapting to continuous cumulation of information and complex relationship queries about them.

To tackle these traditional data managing constraints, Data Chemist combined the relationship-centric view of the Graph database, and the category based rules of the Relational database to create a self-learning software which is more semantically structured. This allows companies to investigate the relationships between millions of data factors through one data model rather than numerous data-handling codes, offering an incredible advantage to data-reliant businesses such as financial and government institutions.

ADAPT wishes the company a successful global launch of its cutting-edge software program.


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