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Databricks > 实例探究 > 现代化数据基础设施以实现个性化人才招聘
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Personalizing Talent Acquisition with IoT: A Case Study of 104 Corporation

技术
  • 分析与建模 - 机器学习
  • 基础设施即服务 (IaaS) - 云计算
适用行业
  • 水泥
  • 教育
适用功能
  • 维护
  • 仓库和库存管理
用例
  • 施工管理
  • 基础设施检查
服务
  • 云规划/设计/实施服务
  • 培训
挑战
104 Corporation 难以有效地扩展管道成本,并在维护操作上花费了大量资源,从而降低了其真正数据驱动的能力。孤立的系统阻止数据团队及时获得相关的见解以做出明智的决策。数据量的增加使得管理和利用变得更加困难。
关于客户
104 Corporation是台湾领先的在线招聘解决方案提供商。他们可以访问数 TB 的高价值私人数据,数百万求职者和数十万招聘人员依赖他们的推荐和个性化工作机会。
解决方案
104 Corporation 在 Databricks Lakehouse 平台上对其基础设施进行了现代化改造,将所有数据统一到下游分析的标准视图中,并确保整个组织中不同团队实时获得见解。他们利用 Databricks Lakehouse 和 Delta Lake 来加速 ETL 和高性能管道。他们还部署了 MLflow,以实现数据科学家、工程师和开发人员之间的协作和知识共享。
运营影响
  • With the shift to the Databricks Lakehouse Platform, 104 Corporation has been able to deliver exceptional hiring experiences to employers and candidates while reducing operational costs. The company has seen faster innovation and has been able to democratize data to match the needs of millions of job seekers and companies. The platform has also enabled seamless, efficient knowledge-sharing across different teams, accelerating prototyping and development of more complex ML and data applications at scale. With curated data at their fingertips and a scalable platform that better supports batch and real-time workloads, data teams can access faster insights, driving more intelligent decisions that impact business operations. The Databricks Lakehouse Platform has become 104 Corporation’s enterprise data platform for information access and exceptional talent acquisition services.
数量效益
  • 9x faster data processing for more personalized job-seeking experiences
  • 25% reduction in time-to-market of new features
  • Average 25% reduction in the amount of time needed to process ETL workloads for both BI dashboarding and ML model training

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