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Firebolt > 实例探究 > How Audiohook uses Firebolt to prepare reports in no time

How Audiohook uses Firebolt to prepare reports in no time

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公司规模
Startup
地区
  • America
国家
  • United States
产品
  • Firebolt
  • AWS S3
  • Firebolt Python SDK
技术栈
  • ELT Datapipe
  • Sparse Indexing
  • Composite Primary Index
实施规模
  • Enterprise-wide Deployment
影响指标
  • Cost Savings
  • Customer Satisfaction
  • Productivity Improvements
技术
  • 平台即服务 (PaaS) - 数据管理平台
  • 分析与建模 - 预测分析
适用行业
  • Software
  • 电信
适用功能
  • 商业运营
  • 销售与市场营销
服务
  • 云规划/设计/实施服务
  • 软件设计与工程服务
  • 系统集成
关于客户
Audiohook is a startup adtech company that focuses on enabling performance marketers to leverage digital audio as a new channel. They provide services that allow businesses to reach customers across digital and traditional audio channels, offering DSP services to enhance these experiences. The company is dedicated to providing insights into marketing campaigns, helping marketers understand the reach and effectiveness of their efforts. As a startup, Audiohook prioritizes dynamic data models and rapid analysis to stay competitive in the fast-paced adtech industry.
挑战
Audiohook, an adtech company, faced challenges with their existing cloud data warehouse, which was unable to meet their performance needs for dynamic data models and speed of analysis. The company needed a solution that could handle complex joins, windows, and aggregations across large event-based datasets to provide insights into marketing campaign effectiveness. Their existing solution was slow, taking up to an hour to compute impressions and conversions, which was not sustainable for their business needs.
解决方案
Audiohook adopted Firebolt, a data warehouse solution running on AWS S3, to address their performance challenges. Firebolt's indexing capabilities, particularly its primary sparse indexing, allowed Audiohook to significantly improve the efficiency of their ELT processes. By leveraging Firebolt's ability to prune unnecessary records and optimize data model design, Audiohook reduced query times from an hour to approximately two minutes. Additionally, Firebolt's model of allowing customers to adjust compute instance attributes enabled Audiohook to choose an engine with more RAM, further enhancing query performance by avoiding intermediate result spilling to disk.
运营影响
  • Audiohook improved the efficiency of their ELT processes, allowing for faster and more accurate data analysis.
  • The adoption of Firebolt enabled Audiohook to provide more dynamic and complex queries to their customers, enhancing the insights available to them.
  • Firebolt's cost-efficiency and low total cost of ownership made it a sustainable choice for Audiohook's data management needs.
数量效益
  • Firebolt reduced query times from an hour to approximately two minutes.
  • Firebolt's indexing capabilities sped up ELT queries by 30x.

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