Fraud Analytics using Accumulo, Julia and Fast SQL

Back to Schedule


Use Case


Argyle fraud solution extends Accumulo's scalable data management to new analytic areas. Julia machine learning models used for identifying telecom and financial services fraud leverage instant rowkey lookups from Accumulo, while distributed SQL engine provides interface for common data visualization tools.


Arshak Navruzyan
VP of Products, Argyle Data

My objective is to make machine learning accessible to any organization or individual that wants to transform the world through data.

I am currently VP of Products at Argyle Data focused on petabyte-scale fraud applications using machine learning and Accumulo. Previously I held senior engineering and product management roles at Alpine Data Labs, Endeca and Oracle.