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Firebolt > 实例探究 > Market Intelligence Company Enhances Analytics Capabilities with Firebolt for Segment Analytics

Market Intelligence Company Enhances Analytics Capabilities with Firebolt for Segment Analytics

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公司规模
Large Corporate
国家
  • United States
产品
  • Firebolt
  • Elasticsearch
  • BigQuery
技术栈
  • SQL
  • AWS Lambda
  • REST APIs
实施规模
  • Enterprise-wide Deployment
影响指标
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
技术
  • 分析与建模 - 预测分析
  • 平台即服务 (PaaS) - 数据管理平台
适用行业
  • Software
  • Professional Service
适用功能
  • 商业运营
服务
  • 云规划/设计/实施服务
  • 软件设计与工程服务
关于客户
The customer is a leading market research technology company that provides digital market intelligence about millions of websites and mobile apps to thousands of clients worldwide. They capture a wide range of online information, including ad, search, and website traffic, and consolidate it into fast, interactive analytics. The company serves a diverse clientele, offering insights that help businesses understand market trends, customer behavior, and competitive landscapes. Their services are crucial for clients looking to make data-driven decisions and optimize their digital strategies. The company is known for its innovative approach to market research and its ability to deliver comprehensive analytics solutions.
挑战
The company faced limitations with its homegrown analytics solution, which restricted its offering and market growth. The existing system was fast for specific queries but limited in the types of analytics and data size it could support. Onboarding new customers was challenging and time-consuming due to the need for extensive customization. Adding new analytics features required significant custom work, and scalability issues limited data sizes and types of analytics. The company evaluated various solutions, including Elasticsearch and BigQuery, but found them either too expensive or not suitable for their needs.
解决方案
The company adopted Firebolt for segment analytics, allowing them to better understand customer behavior, preferences, loyalty, and cross-selling opportunities. They now manage over 200TB of customer data in Firebolt, which has increased as they add data previously unsupported by their old solution. The use of SQL for ELT processes and REST APIs for accessing analytics has significantly improved their agility. Firebolt's native support for JSON and lambda array functions in SQL enabled faster customer onboarding and personalization. The company can now roll out new analytics features in days instead of months, thanks to Firebolt's flexibility and performance. The decoupled storage and compute architecture of Firebolt allows for efficient data management and faster query performance, supporting the company's need to scale and provide better service to its customers.
运营影响
  • The company achieved faster time to market for new features, reducing the rollout time from 6-9 months to just a few days.
  • Customer onboarding became much faster due to automation, eliminating weeks of custom development.
  • The use of Firebolt's SQL and REST APIs allowed for greater agility and flexibility in analytics operations.
  • The company can now handle any data their customers need and analyze up to three years of data efficiently.
  • Firebolt's architecture supports efficient scaling, allowing the company to assign customers to different engines and optimize query performance.
数量效益
  • Firebolt demonstrated 2-3x faster ingestion and 3-70x faster query performance compared to BigQuery.
  • Firebolt was 5x lower in infrastructure costs compared to the existing system.
  • Firebolt was up to 20x less expensive than the alternatives evaluated.

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