MandM Direct：使用 Dataiku + GCP 大规模管理模型
公司规模
Large Corporate
地区
- Europe
国家
- United Kingdom
产品
- Dataiku
- Google Cloud Platform (GCP)
- Google BigQuery
技术栈
- Python
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 零售
适用功能
- 销售与市场营销
- 商业运营
用例
- 预测性维护
- 库存管理
- 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
MandM Direct 是英国最大的在线零售商之一，拥有超过 350 万活跃客户和七个专门的欧洲本地市场网站。该公司每年向全球 25 多个国家/地区提供 300 多个品牌。2020 年，他们经历了快速增长，客户和数据量增加。这种增长加剧了他们的一些挑战，并迫使他们寻找更具可扩展性的解决方案。核心数据团队由四人组成（两名数据科学家、一名高级分析师和一名数据分析师），但他们通过利用中心辐射模型作为其数据中心卓越中心来扩大其覆盖范围，这意味着他们与嵌入在业务线中的分析师合作以扩大他们的工作。
挑战
MandM Direct 是英国最大的在线零售商之一，在快速发展的过程中面临着巨大的挑战。该公司在欧洲拥有超过 350 万活跃客户和 7 个专门的本地市场网站，每年向全球 25 多个国家/地区提供 300 多个品牌。他们的加速增长意味着更多的客户，因此也意味着更多的数据，这加剧了他们的一些挑战，并迫使他们寻找更具可扩展性的解决方案。两个主要挑战是将所有可用数据从孤岛中转移到统一的、可用于分析的环境中，并以可跟踪、透明和协作的方式扩展 AI 部署。最初，该公司的首批机器学习模型是用 Python（.py 文件）编写的，并在数据科学家的本地机器上运行。然而，随着生产中模型数量的增加，团队很快意识到维护模型的负担。
解决方案
为了应对挑战，MandM Direct 选择了 Dataiku 和 Google Cloud Platform (GCP) 的强大组合。借助 Google BigQuery 完全托管的无服务器数据仓库，MandM 可以打破数据孤岛，实现团队间数据访问的民主化。同时，得益于 Dataiku 用于数据管道、数据准备、模型训练和 MLOps 的可视化协作界面，MandM 还可以轻松地在生产中扩展其模型，并且透明且可追溯，不会出现故障或中断。MandM 现在拥有数百个实时模型，可以执行从评估客户倾向到生成定价模型等所有操作，所有这些都可以查看模型性能指标，明确区分设计和生产环境，并且平台中还内置了更多 MLOps 功能。现在，团队可以轻松地将数据准备和机器学习的计算推送和卸载到 GCP。
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