nClouds AWS Case Study | CyberCube
CyberCube is focused on solving the most difficult and important cyber risk challenges in insurance with world-class analytics.
Their team is comprised of multi-disciplinary experts across data science, cybersecurity, software engineering, actuarial modeling, and commercial insurance. CyberCube offers a software-as-a-service (SaaS) platform for cyber risk aggregation modeling and insurance underwriting.
The platform was established in 2015 by Symantec to apply the cybersecurity company’s unique sources of data, intelligence and expertise to cyber insurance analytics, and now operates as a standalone company. To learn more, go to https://www.cybcube.com/
Accelerated data analytics
Reduced data prep time
CyberCube wanted to support its strategic growth by enabling their analysts to build insights that deliver additional value to their customers via new services on their cyber risk analytics platform.
They needed a solution that could easily scale to their size requirements in a transient model, handle data of virtually any type, store massive amounts of data at a low cost, and extract basic models from the data itself to create the ability to query without a lot of transformation.
“As a result of our collaboration with nClouds, we can offer our customers new insights and services. And, we can deliver analytics results faster and at a lower cost. All of this is important to CyberCube’s continued growth.”
CyberCube engaged with nClouds to create a data processing pipeline that enabled easier access to their data to build insights that deliver new value to their customers.
nClouds implemented AWS Glue ETL service to prepare and load CyberCube’s data for analytics. AWS Glue runs ETL jobs in an Apache Spark serverless environment. This service structures different formats of datasets in a common way and puts a metadata layer on top of it (the AWS Glue Data Catalog) so that all data can be accessed in the same way.
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