Heetch + Dataiku：制定弹性 AI 战略
公司规模
200-1,000
地区
- Europe
国家
- France
产品
- Dataiku
- Kubernetes
- AWS EKS
技术栈
- Python
- R
- Spark
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Digital Expertise
- Productivity Improvements
技术
- 基础设施即服务 (IaaS) - 云计算
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 运输
适用功能
- 商业运营
用例
- 车队管理
- 预测性维护
- 供应链可见性(SCV)
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
Heetch 是一家法国公司，成立于 2013 年，旨在通过提供流畅的用户体验让出行更加便捷。自成立以来，该公司迅速发展到拥有 250 名员工，并从司机、乘客、全球运营等各个方面收集了大量数据。然而，随着数据量的增长，该公司难以扩展利用这些数据的能力。五年来，数据仓库成本不断上升，性能也受到影响。该公司需要找到一种解决方案，让组织中的任何人都能处理大量数据，同时确保优化资源分配。
挑战
Heetch 是一家成立于 2013 年的法国公司，目前已迅速发展到拥有 250 名员工，他们共同致力于一个目标：通过提供流畅的用户体验，让出行更加便捷。自成立以来，该公司已经从司机、乘客、全球运营等各个方面收集了大量数据，但他们却难以扩展实际利用这些数据的能力。五年来，数据仓库成本不断上升，随着数据量的增加，性能也受到影响。该公司需要找到一种解决方案，让组织中的任何人都能处理大量数据，同时确保优化资源分配。
解决方案
2019 年，Heetch 选择 Dataiku 作为其构建数据管道和处理原始数据的唯一平台，并与 Looker 配合使用，以实现这些流程的无缝可视化和探索。除了作为 Heetch 可以集中知识和最佳实践的平台之外，该团队还利用 Dataiku 和 Kubernetes 来解决他们的主要痛点：利用数据，同时保持良好的性能和合理的成本。得益于 Dataiku 与主要云供应商的托管 Kubernetes 服务的原生集成，Heetch 能够非常快速地集成其 AWS EKS 集群，并看到其数据的价值大幅提升。团队现在可以轻松卸载资源密集型工作负载，例如大型 Python 和 R 作业，以及利用 EKS 集群来分配计算和运行 Spark 作业。使用 Dataiku 意味着任何 Heetch 员工都可以使用和访问此功能，无论他或她在分布式计算方面的知识如何 - Dataiku 消除了复杂性。
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