Delivering Insurance Policies Online Using Real-Time Data Insights
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- Snowflake
- AtScale
- Tableau
- Excel
技术栈
- Python
- MySQL
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
- Customer Satisfaction
技术
- 基础设施即服务 (IaaS) - 云计算
- 分析与建模 - 大数据分析
适用功能
- 商业运营
- 销售与市场营销
用例
- 机器翻译
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
EverQuote is one of the largest online marketplaces for insurance. The company empowers customers to better protect their most important assets, such as their family, property, or future. Through the use of data and technology, EverQuote aims to be a trusted source for simple, affordable, and personalized insurance policies. The company was a spinoff from Cogo Labs, a technology-driven venture accelerator, and had a data architecture consisting of a MySQL cluster, Python services, a direct connection to Excel, and a custom OLAP interface.
挑战
EverQuote, a large online marketplace for insurance, was facing challenges with its in-house custom OLAP solution. The system, which was over ten years old, had several bottlenecks that prevented many use cases and suffered from poor query performance. As the company grew, it also found it difficult to scale self-service analytics to non-technical employees. The company needed a modern data architecture that could democratize data analytics for all.
解决方案
EverQuote decided to shift from its in-house OLAP solution to Snowflake’s cloud data platform using AtScale. With AtScale’s Semantic Layer, EverQuote was able to transition its analytics workloads to Snowflake without impacting the existing business user experience. The semantic layer now enables the business team to access data stored on Snowflake within Tableau, Excel, and many other business analytics and visualization tools. Through AtScale’s semantic modeling capabilities, EverQuote is able to flexibly add new metrics and data definitions that provide consistency across consumption tools. Data virtualization also makes it easier to onboard new data quickly so that it can be queried from BI tools almost immediately.
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