A Fortune 100 P&C Insurer Uses AWS ODS for Efficient Operations
Challenge
Continuous innovation in insurance analytics enables many P&C insurers to improve their plans for customer-centricity, telematics, and claim management efficiency. However, P&C insurers often struggle with leveraging enterprise-level data due to inaccessible data formats or a lack of trust in the underlying data quality and semantics.
A Fortune 100 P&C insurer in the US, who we will call WesternShores, needed a next-gen operational data store (ODS). The company’s leaders found it challenging to manage operations efficiently with slow development life cycles, limited data processing capability, and heavy dependence on IT. They were looking for low-cost infrastructure and analytics solutions as they migrated their existing applications to event-based architecture.
Knowing there was a better way, they set out to deploy an intelligent, state-of-the-art ODS and analytics solution.
Our Approach
To foster greater trust among stakeholders, WesternShores collaborated with Trianz to start user research through a focused questionnaire and conducted executive interviews and workshops to uncover key issues and gather data points.
To suggest a smarter analytics solution, WesternShores needed to know the costs of a big data platform on the cloud to make the right choice. They were already using Hadoop-as-a-Service (HDaaS) as an alternative to on-premises Hadoop deployments; however, due to a lack of skilled resources, were struggling to use it to its full advantage.
After evaluating their existing analytics landscape and infrastructure and analyzing data points, we suggested deploying Hortonworks Data Platform (HDP) on Amazon Web Services (AWS) Cloud. We leveraged our proprietary total cost of ownership (TCO) calculator to compare their HDaaS with Hortonworks Data Platform deployed on AWS Elastic Compute Cloud (EC2) to estimate the total cost of ownership (TCO). We also defined a roadmap to deploy the HDP on the cloud.
Considering all the internal and external factors, we proposed three storage options to WesternShores in the Hadoop deployment architectures on AWS:
Simple Storage Service (S3) - Amazon Simple Storage Service or Amazon S3 can store vast numbers of backups or user files, which are readily available when needed. There are no resource procurement cycles or investments upfront, which means they can keep their data safe from errors, failures, and threats. WesternShores can easily hold their content and media files in S3, which may be served efficiently from AWS CloudFront. Plus, S3 can easily create a data lake to hold raw data in its native format and then use machine learning tools, query-in-place, and analytics to draw insights.
Elastic Block Store (EBS) - Amazon’s block-level storage solution, where they can keep the data on the AWS EBS servers even when the EC2 instances are shut down. EBS offers them high availability and low-latency performance within the selected availability zone, allowing them to easily scale storage capacity at a low subscription-based pricing model.
AWS EC2 instance store - An AWS instance store is a temporary storage type located on disks that are physically attached to a host machine. Out of the three instance store volumes, we suggested Ephemeral storage to WesternShores. Also known as virtual devices, this was suitable for low-latency storage.
Transformational Effects
Our ODS best practices and implementations for building an ODS - AWS’ next-gen Hadoop-based platform - resulted in accurate, real time estimates for WesternShores’s TCO in the first year. They also benefitted from our cost projections of operational data storage, resulting in a better performance.
