Wellington based data science company Intela has launched an online tool, Farrago, that uses machine learning to clean up dirty data.
It claims Farrago is able to cope with data of any kind and any context, could stimulate advancement in data science initiatives, and save organisations thousands of hours spent manually identifying and removing duplicate records from databases.
Intela says it has been working on the challenge since mid-2017, after being asked by a large local council to help clean up multiple large datasets in preparation for a core system migration.
“After exploring the problem with organisations of all sizes, it was clear that the pain is felt everywhere and that existing solutions are cumbersome or highly context specific.”
Intela CEO, Asa Cox said dirty data was a well-known issue that could be holding back New Zealand organisations from realising a huge amount of advancement gained from new powerful data applications.
Intela CTO Kameron Christopher added: “Data quality underpins all data centric initiatives and data science itself. Be it predictive analytics, task automation, machine learning or simple customer intelligence; dirty data in, dirty data out.”
An online demonstration of Farrago is available at demo.farrago.ai